---
_id: '65408'
citation:
ama: Menne AL, Schulz C, eds. Unpacking [Digital] Imaginaries. Das Imaginäre
im Kontext digitaler Medien. Transcript
apa: Menne, A. L., & Schulz, C. (Eds.). (n.d.). Unpacking [Digital] Imaginaries.
Das Imaginäre im Kontext digitaler Medien. Transcript.
bibtex: '@book{Menne_Schulz, place={Bielefeld}, title={Unpacking [Digital] Imaginaries.
Das Imaginäre im Kontext digitaler Medien}, publisher={Transcript} }'
chicago: 'Menne, Anna Lena, and Christian Schulz, eds. Unpacking [Digital] Imaginaries.
Das Imaginäre im Kontext digitaler Medien. Bielefeld: Transcript, n.d.'
ieee: 'A. L. Menne and C. Schulz, Eds., Unpacking [Digital] Imaginaries. Das
Imaginäre im Kontext digitaler Medien. Bielefeld: Transcript.'
mla: Menne, Anna Lena, and Christian Schulz, editors. Unpacking [Digital] Imaginaries.
Das Imaginäre im Kontext digitaler Medien. Transcript.
short: A.L. Menne, C. Schulz, eds., Unpacking [Digital] Imaginaries. Das Imaginäre
im Kontext digitaler Medien, Transcript, Bielefeld, n.d.
date_created: 2026-04-13T11:56:12Z
date_updated: 2026-05-24T08:46:06Z
department:
- _id: '757'
- _id: '11'
editor:
- first_name: Anna Lena
full_name: Menne, Anna Lena
id: '118085'
last_name: Menne
orcid: 0009-0008-0744-9165
- first_name: Christian
full_name: Schulz, Christian
id: '72684'
last_name: Schulz
language:
- iso: other
place: Bielefeld
project:
- _id: '109'
name: 'TRR 318: Erklärbarkeit konstruieren'
publication_status: unpublished
publisher: Transcript
status: public
title: Unpacking [Digital] Imaginaries. Das Imaginäre im Kontext digitaler Medien
type: book_editor
user_id: '72684'
year: '2027'
...
---
_id: '65061'
abstract:
- lang: eng
text: "Abstract\r\n \r\n One
of the purposes for which XAI is often brought into play is to enable a user to
act responsibly. However, responsibility is a complex normative and social phenomenon
that we unfold in this chapter. We consider that the classical concepts of agency
and responsibility do not fully capture what is needed for meaningful collaboration
between human users and XAI. Advocating the perspective of sXAI, we argue that
the growing adaptivity of AI systems will result in sXAI being considered as partners.
Both partners adopt particular (dialogical) roles within a collaborative process
and take responsibility for them. We expect that these roles lead to reactive
attitudes toward the sXAI on the side of the human partners that make these roles
relational. They resemble those reactive attitudes that we hold toward other human
agents. For agents to exercise their responsibility, they need to possess agential
capacities to fulfill their role with respect to the structure of a social interaction.
Hence, sXAI can be expected to act responsibly. But because of XAI’s limited normative
capacities, it might rather act as a marginal agent. We refer to marginal agents
and show they can be scaffolded with regard to their agential capacities and their
knowledge about the structure of a social interaction. The structure links the
actions of the partners to each other in terms of a set of stimuli and responses
to it in pursuit of a particular goal. Hence, it is important to differentiate
between the different goals that a structure can impose for exercising responsibility.
Therefore, we follow (Responsibility from the margins. Oxford University Press;
2015.\r\n https://doi.org/10.1093/acprof:oso/9780198715672.24001.0001\r\n
\ ) and offer three structures that can help to organize responsibility
for\r\n decisions made\r\n with
the assistance of AI systems. These structures are attributability, answerability,
and accountability. Our insights will inform the development and design process
of XAI to meet the guiding principles of responsible research and innovation as
well as trustworthy AI.\r\n "
author:
- first_name: Katharina J.
full_name: Rohlfing, Katharina J.
id: '50352'
last_name: Rohlfing
orcid: 0000-0002-5676-8233
- first_name: Suzana
full_name: Alpsancar, Suzana
id: '93637'
last_name: Alpsancar
- first_name: Carsten
full_name: Schulte, Carsten
id: '60311'
last_name: Schulte
citation:
ama: 'Rohlfing KJ, Alpsancar S, Schulte C. Responsibilities in sXAI. In: Social
Explainable AI. Springer Nature Singapore; 2026:157-177. doi:10.1007/978-981-96-5290-7_9'
apa: Rohlfing, K. J., Alpsancar, S., & Schulte, C. (2026). Responsibilities
in sXAI. In Social Explainable AI (pp. 157–177). Springer Nature Singapore.
https://doi.org/10.1007/978-981-96-5290-7_9
bibtex: '@inbook{Rohlfing_Alpsancar_Schulte_2026, place={Singapore}, title={Responsibilities
in sXAI}, DOI={10.1007/978-981-96-5290-7_9},
booktitle={Social Explainable AI}, publisher={Springer Nature Singapore}, author={Rohlfing,
Katharina J. and Alpsancar, Suzana and Schulte, Carsten}, year={2026}, pages={157–177}
}'
chicago: 'Rohlfing, Katharina J., Suzana Alpsancar, and Carsten Schulte. “Responsibilities
in SXAI.” In Social Explainable AI, 157–77. Singapore: Springer Nature
Singapore, 2026. https://doi.org/10.1007/978-981-96-5290-7_9.'
ieee: 'K. J. Rohlfing, S. Alpsancar, and C. Schulte, “Responsibilities in sXAI,”
in Social Explainable AI, Singapore: Springer Nature Singapore, 2026, pp.
157–177.'
mla: Rohlfing, Katharina J., et al. “Responsibilities in SXAI.” Social Explainable
AI, Springer Nature Singapore, 2026, pp. 157–77, doi:10.1007/978-981-96-5290-7_9.
short: 'K.J. Rohlfing, S. Alpsancar, C. Schulte, in: Social Explainable AI, Springer
Nature Singapore, Singapore, 2026, pp. 157–177.'
date_created: 2026-03-19T10:59:18Z
date_updated: 2026-03-19T11:53:01Z
department:
- _id: '26'
- _id: '756'
doi: 10.1007/978-981-96-5290-7_9
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1007/978-981-96-5290-7_9
oa: '1'
page: 157-177
place: Singapore
project:
- _id: '109'
name: 'TRR 318: Erklärbarkeit konstruieren'
- _id: '370'
name: 'TRR 318; TP B06: Ethik und Normativität der erklärbaren KI'
publication: Social Explainable AI
publication_identifier:
isbn:
- '9789819652891'
- '9789819652907'
publication_status: published
publisher: Springer Nature Singapore
status: public
title: Responsibilities in sXAI
type: book_chapter
user_id: '93637'
year: '2026'
...
---
_id: '65064'
abstract:
- lang: eng
text: "Abstract\r\n XAI can minimize
the risks of being manipulated and deceived by AI but in turn entails other specific
risks. This also applies to sXAI, and the specifically social character of sXAI
harbors particular risks that designers and developers should be aware of. In
this chapter, we shall discuss the potential opportunities and risks of sXAI.
We see a particularly positive potential in the social character of sXAI, which
lies in the fact that skillful users, including those with “healthy distrust,”
can use the adaptivity of sXAI to produce an explanation that is actually relevant
and adequate for them. However, this requires a high level of skills on the part
of the user and is thus in contrast to the general promise of efficiency in the
use of AI. A potential risk of XAI is that it can be (even more) persuasive, as
the interactive involvement and the anthropomorphism strengthen a trustworthy
appearance/performance (independent of the adequacy of the sXAI performance)."
author:
- first_name: Suzana
full_name: Alpsancar, Suzana
id: '93637'
last_name: Alpsancar
- first_name: Michael
full_name: Klenk, Michael
last_name: Klenk
citation:
ama: 'Alpsancar S, Klenk M. The Risk of Manipulation and Deception in sXAI. In:
Social Explainable AI. Springer Nature Singapore; 2026:583-616. doi:10.1007/978-981-96-5290-7_30'
apa: Alpsancar, S., & Klenk, M. (2026). The Risk of Manipulation and Deception
in sXAI. In Social Explainable AI (pp. 583–616). Springer Nature Singapore.
https://doi.org/10.1007/978-981-96-5290-7_30
bibtex: '@inbook{Alpsancar_Klenk_2026, place={Singapore}, title={The Risk of Manipulation
and Deception in sXAI}, DOI={10.1007/978-981-96-5290-7_30},
booktitle={Social Explainable AI}, publisher={Springer Nature Singapore}, author={Alpsancar,
Suzana and Klenk, Michael}, year={2026}, pages={583–616} }'
chicago: 'Alpsancar, Suzana, and Michael Klenk. “The Risk of Manipulation and Deception
in SXAI.” In Social Explainable AI, 583–616. Singapore: Springer Nature
Singapore, 2026. https://doi.org/10.1007/978-981-96-5290-7_30.'
ieee: 'S. Alpsancar and M. Klenk, “The Risk of Manipulation and Deception in sXAI,”
in Social Explainable AI, Singapore: Springer Nature Singapore, 2026, pp.
583–616.'
mla: Alpsancar, Suzana, and Michael Klenk. “The Risk of Manipulation and Deception
in SXAI.” Social Explainable AI, Springer Nature Singapore, 2026, pp. 583–616,
doi:10.1007/978-981-96-5290-7_30.
short: 'S. Alpsancar, M. Klenk, in: Social Explainable AI, Springer Nature Singapore,
Singapore, 2026, pp. 583–616.'
date_created: 2026-03-19T11:05:30Z
date_updated: 2026-03-19T11:52:00Z
department:
- _id: '26'
- _id: '756'
doi: 10.1007/978-981-96-5290-7_30
language:
- iso: eng
main_file_link:
- open_access: '1'
url: ' https://doi.org/10.1007/978-981-96-5290-7_30'
oa: '1'
page: 583-616
place: Singapore
project:
- _id: '109'
name: 'TRR 318: Erklärbarkeit konstruieren'
- _id: '370'
name: 'TRR 318; TP B06: Ethik und Normativität der erklärbaren KI'
publication: Social Explainable AI
publication_identifier:
isbn:
- '9789819652891'
- '9789819652907'
publication_status: published
publisher: Springer Nature Singapore
status: public
title: The Risk of Manipulation and Deception in sXAI
type: book_chapter
user_id: '93637'
year: '2026'
...
---
_id: '65065'
abstract:
- lang: eng
text: "Abstract\r\n This introduction
sets the stage for the present book. Whereas research in eXplainable AI (XAI)
is motivated by societal changes and values, technology development largely ignores
social aspects. This book aims to address this research gap with a systematic
and comprehensive social view on explainable AI. Besides introducing many relevant
concepts, the book offers first access to their possible implementation, thus
advancing the development of more social XAI. The introduction starts by connecting
the topic to the general research field of XAI. The second part defines the novel
approach of social eXplainable AI (sXAI) along the three characteristics of social
interaction such as patternedness, incrementality, and multimodality. Finally,
the third part explains the structure followed by each chapter. The book offers
insights not only for readers who work on technology development but also for
those working in sociotechnical fields. Addressing an interdisciplinary readership,
the book is an invitation for more exchange and further development of the sXAI
field."
citation:
ama: Rohlfing KJ, Främling K, Lim B, Alpsancar S, Thommes K, eds. Social Explainable
AI. Springer Nature Singapore; 2026. doi:10.1007/978-981-96-5290-7_1
apa: Rohlfing, K. J., Främling, K., Lim, B., Alpsancar, S., & Thommes, K. (Eds.).
(2026). Social Explainable AI. Springer Nature Singapore. https://doi.org/10.1007/978-981-96-5290-7_1
bibtex: '@book{Rohlfing_Främling_Lim_Alpsancar_Thommes_2026, place={Singapore},
title={Social Explainable AI}, DOI={10.1007/978-981-96-5290-7_1},
publisher={Springer Nature Singapore}, year={2026} }'
chicago: 'Rohlfing, Katharina J., Kary Främling, Brian Lim, Suzana Alpsancar, and
Kirsten Thommes, eds. Social Explainable AI. Singapore: Springer Nature
Singapore, 2026. https://doi.org/10.1007/978-981-96-5290-7_1.'
ieee: 'K. J. Rohlfing, K. Främling, B. Lim, S. Alpsancar, and K. Thommes, Eds.,
Social Explainable AI. Singapore: Springer Nature Singapore, 2026.'
mla: Rohlfing, Katharina J., et al., editors. Social Explainable AI. Springer
Nature Singapore, 2026, doi:10.1007/978-981-96-5290-7_1.
short: K.J. Rohlfing, K. Främling, B. Lim, S. Alpsancar, K. Thommes, eds., Social
Explainable AI, Springer Nature Singapore, Singapore, 2026.
date_created: 2026-03-19T11:55:17Z
date_updated: 2026-03-19T11:59:42Z
department:
- _id: '26'
- _id: '756'
doi: 10.1007/978-981-96-5290-7_1
editor:
- first_name: Katharina J.
full_name: Rohlfing, Katharina J.
id: '50352'
last_name: Rohlfing
orcid: 0000-0002-5676-8233
- first_name: Kary
full_name: Främling, Kary
last_name: Främling
- first_name: Brian
full_name: Lim, Brian
last_name: Lim
- first_name: Suzana
full_name: Alpsancar, Suzana
id: '93637'
last_name: Alpsancar
- first_name: Kirsten
full_name: Thommes, Kirsten
id: '72497'
last_name: Thommes
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://link.springer.com/book/10.1007/978-981-96-5290-7
oa: '1'
place: Singapore
project:
- _id: '109'
name: 'TRR 318: Erklärbarkeit konstruieren'
publication_identifier:
isbn:
- '9789819652891'
- '9789819652907'
publication_status: published
publisher: Springer Nature Singapore
status: public
title: Social Explainable AI
type: book_editor
user_id: '93637'
year: '2026'
...
---
_id: '55598'
author:
- first_name: Christian
full_name: Schulz, Christian
id: '72684'
last_name: Schulz
citation:
ama: 'Schulz C. Feeds. Ein zentrales Strukturprinzip sozialer Medien. In: Dörre
R, Tuschling A, eds. Handbuch Social Media: Geschichte – Kultur – Ästhetik.
1st ed. Metzler Verlag.'
apa: 'Schulz, C. (n.d.). Feeds. Ein zentrales Strukturprinzip sozialer Medien. In
R. Dörre & A. Tuschling (Eds.), Handbuch Social Media: Geschichte – Kultur
– Ästhetik (1st ed.). Metzler Verlag.'
bibtex: '@inbook{Schulz, place={Stuttgart}, edition={1}, title={Feeds. Ein zentrales
Strukturprinzip sozialer Medien}, booktitle={Handbuch Social Media: Geschichte
– Kultur – Ästhetik}, publisher={Metzler Verlag}, author={Schulz, Christian},
editor={Dörre, Robert and Tuschling, Anna } }'
chicago: 'Schulz, Christian. “Feeds. Ein zentrales Strukturprinzip sozialer Medien.”
In Handbuch Social Media: Geschichte – Kultur – Ästhetik, edited by Robert
Dörre and Anna Tuschling, 1st ed. Stuttgart: Metzler Verlag, n.d.'
ieee: 'C. Schulz, “Feeds. Ein zentrales Strukturprinzip sozialer Medien,” in Handbuch
Social Media: Geschichte – Kultur – Ästhetik, 1st ed., R. Dörre and A. Tuschling,
Eds. Stuttgart: Metzler Verlag.'
mla: 'Schulz, Christian. “Feeds. Ein zentrales Strukturprinzip sozialer Medien.”
Handbuch Social Media: Geschichte – Kultur – Ästhetik, edited by Robert
Dörre and Anna Tuschling, 1st ed., Metzler Verlag.'
short: 'C. Schulz, in: R. Dörre, A. Tuschling (Eds.), Handbuch Social Media: Geschichte
– Kultur – Ästhetik, 1st ed., Metzler Verlag, Stuttgart, n.d.'
date_created: 2024-08-14T06:10:18Z
date_updated: 2026-03-21T08:30:12Z
edition: '1'
editor:
- first_name: Robert
full_name: Dörre, Robert
last_name: Dörre
- first_name: 'Anna '
full_name: 'Tuschling, Anna '
last_name: Tuschling
language:
- iso: ger
place: Stuttgart
project:
- _id: '109'
name: 'TRR 318: TRR 318 - Erklärbarkeit konstruieren'
publication: 'Handbuch Social Media: Geschichte – Kultur – Ästhetik'
publication_status: unpublished
publisher: Metzler Verlag
status: public
title: Feeds. Ein zentrales Strukturprinzip sozialer Medien
type: book_chapter
user_id: '72684'
year: '2026'
...
---
_id: '65544'
author:
- first_name: Markus
full_name: Knauff, Markus
last_name: Knauff
- first_name: Martin V.
full_name: Butz, Martin V.
last_name: Butz
- first_name: Barbara
full_name: Kaup, Barbara
last_name: Kaup
- first_name: Wilfried
full_name: Kunde, Wilfried
last_name: Kunde
- first_name: Ingrid
full_name: Scharlau, Ingrid
id: '451'
last_name: Scharlau
orcid: 0000-0003-2364-9489
citation:
ama: Knauff M, Butz MV, Kaup B, Kunde W, Scharlau I. When prediction replaces explanation:
A threat to psychological science . psyarxiv. Published online 2026.
apa: Knauff, M., Butz, M. V., Kaup, B., Kunde, W., & Scharlau, I. (2026). When
prediction replaces explanation: A threat to psychological science . In psyarxiv.
OSF.
bibtex: '@article{Knauff_Butz_Kaup_Kunde_Scharlau_2026, title={When prediction replaces
explanation: A threat to psychological science }, journal={psyarxiv}, publisher={OSF},
author={Knauff, Markus and Butz, Martin V. and Kaup, Barbara and Kunde, Wilfried
and Scharlau, Ingrid}, year={2026} }'
chicago: Knauff, Markus, Martin V. Butz, Barbara Kaup, Wilfried Kunde, and Ingrid
Scharlau. “When Prediction Replaces Explanation: A Threat to Psychological Science
.” Psyarxiv. OSF, 2026.
ieee: M. Knauff, M. V. Butz, B. Kaup, W. Kunde, and I. Scharlau, “When prediction
replaces explanation: A threat to psychological science ,” psyarxiv. OSF,
2026.
mla: Knauff, Markus, et al. “When Prediction Replaces Explanation: A Threat to
Psychological Science .” Psyarxiv, OSF, 2026.
short: M. Knauff, M.V. Butz, B. Kaup, W. Kunde, I. Scharlau, Psyarxiv (2026).
date_created: 2026-05-01T08:10:05Z
date_updated: 2026-05-01T08:10:11Z
department:
- _id: '424'
keyword:
- explainability
- explanation
- prediction
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://osf.io/preprints/psyarxiv/v2pht_v1
oa: '1'
page: '18'
project:
- _id: '124'
name: 'TRR 318 ; TP C01: Gesundes Misstrauen in Erklärungen'
- _id: '109'
name: 'TRR 318: Erklärbarkeit konstruieren'
- _id: '127'
name: 'TRR 318; TP C04: Metaphern als Werkzeug des Erklärens'
publication: psyarxiv
publisher: OSF
status: public
title: 'When prediction replaces explanation: A threat to psychological science '
type: preprint
user_id: '451'
year: '2026'
...
---
_id: '64789'
author:
- first_name: Fabian
full_name: Beer, Fabian
last_name: Beer
- first_name: Christian
full_name: Schulz, Christian
id: '72684'
last_name: Schulz
citation:
ama: 'Beer F, Schulz C. AI has never been inherently interpretable: On a paradoxical
origin of eXplainable AI (XAI). RESET Journal (Recherches sciences sociale
sur internet) Special Issue: Towards New Social and Historical Studies of Artificial
Intelligence.'
apa: 'Beer, F., & Schulz, C. (n.d.). AI has never been inherently interpretable:
On a paradoxical origin of eXplainable AI (XAI). RESET Journal (Recherches
Sciences Sociale Sur Internet) Special Issue: Towards New Social and Historical
Studies of Artificial Intelligence.'
bibtex: '@article{Beer_Schulz, title={AI has never been inherently interpretable:
On a paradoxical origin of eXplainable AI (XAI)}, journal={RESET Journal (Recherches
sciences sociale sur internet) Special Issue: Towards New Social and Historical
Studies of Artificial Intelligence}, publisher={Open Edition Journals}, author={Beer,
Fabian and Schulz, Christian} }'
chicago: 'Beer, Fabian, and Christian Schulz. “AI Has Never Been Inherently Interpretable:
On a Paradoxical Origin of EXplainable AI (XAI).” RESET Journal (Recherches
Sciences Sociale Sur Internet) Special Issue: Towards New Social and Historical
Studies of Artificial Intelligence, n.d.'
ieee: 'F. Beer and C. Schulz, “AI has never been inherently interpretable: On a
paradoxical origin of eXplainable AI (XAI),” RESET Journal (Recherches sciences
sociale sur internet) Special Issue: Towards New Social and Historical Studies
of Artificial Intelligence.'
mla: 'Beer, Fabian, and Christian Schulz. “AI Has Never Been Inherently Interpretable:
On a Paradoxical Origin of EXplainable AI (XAI).” RESET Journal (Recherches
Sciences Sociale Sur Internet) Special Issue: Towards New Social and Historical
Studies of Artificial Intelligence, Open Edition Journals.'
short: 'F. Beer, C. Schulz, RESET Journal (Recherches Sciences Sociale Sur Internet)
Special Issue: Towards New Social and Historical Studies of Artificial Intelligence
(n.d.).'
date_created: 2026-02-28T09:14:38Z
date_updated: 2026-05-25T11:49:36Z
department:
- _id: '11'
- _id: '757'
language:
- iso: eng
project:
- _id: '109'
name: 'TRR 318: Erklärbarkeit konstruieren'
publication: 'RESET Journal (Recherches sciences sociale sur internet) Special Issue:
Towards New Social and Historical Studies of Artificial Intelligence'
publication_status: accepted
publisher: Open Edition Journals
status: public
title: 'AI has never been inherently interpretable: On a paradoxical origin of eXplainable
AI (XAI)'
type: journal_article
user_id: '72684'
year: '2026'
...
---
_id: '63031'
abstract:
- lang: eng
text: Despite decades of awareness, asymmetries in conceptual resources, data, and
governance between users and developers persist. Meanwhile, socially situated
‘end-users’ experience harms, such as hidden labor, reinforced stereotypes, and
increased unpredictability, as machine learning advances. However, accurately
modeling social context does not constitute design justice. This paper reinterprets
Giuseppe Mantovani’s model of social context in human-computer interaction (HCI)
to address the relational emergence and political situatedness of social context
in human-AI interaction (HAI). Drawing on the concept of a multi-perspectival
algorithmic imaginary, we (1) conceptualize context as nested and entangled relations,
(2) identify actors, including users, developers, models, and interfaces, and
(3) foreground the organization of relations of power. Recognizing that models
are performative rather than predictive, we argue that the sociopolitical situatedness
of context must be acknowledged alongside its limits. To challenge design authority,
we propose that HCI and HAI strategically foster intra-actional negotiability,
enabling users to challenge, reinterpret, or modify their relationship with technology
through critical (design) practices.
author:
- first_name: Anna Lena
full_name: Menne, Anna Lena
id: '118085'
last_name: Menne
orcid: 0009-0008-0744-9165
- first_name: Christian
full_name: Schulz, Christian
id: '72684'
last_name: Schulz
citation:
ama: 'Menne AL, Schulz C. Social Context in Human-AI Interaction (HAI): Towards
a Theoretical Framework Based on Multi-Perspectival Imaginaries. In: Stephanidis
C, Margetis G, Ntoa S, Antona M, Salvendy G, eds. HCI International 2026 Posters:
28th International Conference on Human-Computer Interaction, HCII 2026, Montreal,
QC, Canada, July 26–31, 2026, Proceedings, Part I. Vol 3047. Communications
in Computer and Information Science (CCIS). Springer International Publishing;
2026:93-106. doi:10.1007/978-3-032-30552-7_10'
apa: 'Menne, A. L., & Schulz, C. (2026). Social Context in Human-AI Interaction
(HAI): Towards a Theoretical Framework Based on Multi-Perspectival Imaginaries.
In C. Stephanidis, G. Margetis, S. Ntoa, M. Antona, & G. Salvendy (Eds.),
HCI International 2026 Posters: 28th International Conference on Human-Computer
Interaction, HCII 2026, Montreal, QC, Canada, July 26–31, 2026, Proceedings, Part
I (Vol. 3047, pp. 93–106). Springer International Publishing. https://doi.org/10.1007/978-3-032-30552-7_10'
bibtex: '@inbook{Menne_Schulz_2026, series={Communications in Computer and Information
Science (CCIS)}, title={Social Context in Human-AI Interaction (HAI): Towards
a Theoretical Framework Based on Multi-Perspectival Imaginaries}, volume={3047},
DOI={10.1007/978-3-032-30552-7_10},
booktitle={HCI International 2026 Posters: 28th International Conference on Human-Computer
Interaction, HCII 2026, Montreal, QC, Canada, July 26–31, 2026, Proceedings, Part
I}, publisher={Springer International Publishing}, author={Menne, Anna Lena and
Schulz, Christian}, editor={Stephanidis, Constantine and Margetis, George and
Ntoa, Stavroula and Antona, Margherita and Salvendy, Gavriel}, year={2026}, pages={93–106},
collection={Communications in Computer and Information Science (CCIS)} }'
chicago: 'Menne, Anna Lena, and Christian Schulz. “Social Context in Human-AI Interaction
(HAI): Towards a Theoretical Framework Based on Multi-Perspectival Imaginaries.”
In HCI International 2026 Posters: 28th International Conference on Human-Computer
Interaction, HCII 2026, Montreal, QC, Canada, July 26–31, 2026, Proceedings, Part
I, edited by Constantine Stephanidis, George Margetis, Stavroula Ntoa, Margherita
Antona, and Gavriel Salvendy, 3047:93–106. Communications in Computer and Information
Science (CCIS). Springer International Publishing, 2026. https://doi.org/10.1007/978-3-032-30552-7_10.'
ieee: 'A. L. Menne and C. Schulz, “Social Context in Human-AI Interaction (HAI):
Towards a Theoretical Framework Based on Multi-Perspectival Imaginaries,” in HCI
International 2026 Posters: 28th International Conference on Human-Computer Interaction,
HCII 2026, Montreal, QC, Canada, July 26–31, 2026, Proceedings, Part I, vol.
3047, C. Stephanidis, G. Margetis, S. Ntoa, M. Antona, and G. Salvendy, Eds. Springer
International Publishing, 2026, pp. 93–106.'
mla: 'Menne, Anna Lena, and Christian Schulz. “Social Context in Human-AI Interaction
(HAI): Towards a Theoretical Framework Based on Multi-Perspectival Imaginaries.”
HCI International 2026 Posters: 28th International Conference on Human-Computer
Interaction, HCII 2026, Montreal, QC, Canada, July 26–31, 2026, Proceedings, Part
I, edited by Constantine Stephanidis et al., vol. 3047, Springer International
Publishing, 2026, pp. 93–106, doi:10.1007/978-3-032-30552-7_10.'
short: 'A.L. Menne, C. Schulz, in: C. Stephanidis, G. Margetis, S. Ntoa, M. Antona,
G. Salvendy (Eds.), HCI International 2026 Posters: 28th International Conference
on Human-Computer Interaction, HCII 2026, Montreal, QC, Canada, July 26–31, 2026,
Proceedings, Part I, Springer International Publishing, 2026, pp. 93–106.'
conference:
end_date: 2026-07-31
location: Montreal
name: 'HCI International 2026: 28th International Conference on Human-Computer Interaction'
start_date: 2026-07-26
date_created: 2025-12-11T10:14:17Z
date_updated: 2026-07-23T10:02:20Z
department:
- _id: '757'
doi: 10.1007/978-3-032-30552-7_10
editor:
- first_name: 'Constantine '
full_name: 'Stephanidis, Constantine '
last_name: Stephanidis
- first_name: George
full_name: Margetis, George
last_name: Margetis
- first_name: Stavroula
full_name: Ntoa, Stavroula
last_name: Ntoa
- first_name: Margherita
full_name: Antona, Margherita
last_name: Antona
- first_name: Gavriel
full_name: Salvendy, Gavriel
last_name: Salvendy
intvolume: ' 3047'
keyword:
- Social Context
- Situatedness
- Imaginaries
language:
- iso: eng
main_file_link:
- url: https://link.springer.com/chapter/10.1007/978-3-032-30552-7_10
page: 93-106
project:
- _id: '109'
name: 'TRR 318: Erklärbarkeit konstruieren'
publication: 'HCI International 2026 Posters: 28th International Conference on Human-Computer
Interaction, HCII 2026, Montreal, QC, Canada, July 26–31, 2026, Proceedings, Part
I'
publication_status: published
publisher: Springer International Publishing
series_title: Communications in Computer and Information Science (CCIS)
status: public
title: 'Social Context in Human-AI Interaction (HAI): Towards a Theoretical Framework
Based on Multi-Perspectival Imaginaries'
type: book_chapter
user_id: '118085'
volume: 3047
year: '2026'
...
---
_id: '61229'
author:
- first_name: Maximilian
full_name: Muschalik, Maximilian
last_name: Muschalik
- first_name: Fabian
full_name: Fumagalli, Fabian
last_name: Fumagalli
- first_name: Paolo
full_name: Frazzetto, Paolo
last_name: Frazzetto
- first_name: Janine
full_name: Strotherm, Janine
last_name: Strotherm
- first_name: Luca
full_name: Hermes, Luca
last_name: Hermes
- first_name: Alessandro
full_name: Sperduti, Alessandro
last_name: Sperduti
- first_name: Eyke
full_name: Hüllermeier, Eyke
last_name: Hüllermeier
- first_name: Barbara
full_name: Hammer, Barbara
last_name: Hammer
citation:
ama: 'Muschalik M, Fumagalli F, Frazzetto P, et al. Exact Computation of Any-Order
Shapley Interactions for Graph Neural Networks. In: The Thirteenth International
Conference on Learning Representations (ICLR). ; 2025.'
apa: Muschalik, M., Fumagalli, F., Frazzetto, P., Strotherm, J., Hermes, L., Sperduti,
A., Hüllermeier, E., & Hammer, B. (2025). Exact Computation of Any-Order Shapley
Interactions for Graph Neural Networks. The Thirteenth International Conference
on Learning Representations (ICLR).
bibtex: '@inproceedings{Muschalik_Fumagalli_Frazzetto_Strotherm_Hermes_Sperduti_Hüllermeier_Hammer_2025,
title={Exact Computation of Any-Order Shapley Interactions for Graph Neural Networks},
booktitle={The Thirteenth International Conference on Learning Representations
(ICLR)}, author={Muschalik, Maximilian and Fumagalli, Fabian and Frazzetto, Paolo
and Strotherm, Janine and Hermes, Luca and Sperduti, Alessandro and Hüllermeier,
Eyke and Hammer, Barbara}, year={2025} }'
chicago: Muschalik, Maximilian, Fabian Fumagalli, Paolo Frazzetto, Janine Strotherm,
Luca Hermes, Alessandro Sperduti, Eyke Hüllermeier, and Barbara Hammer. “Exact
Computation of Any-Order Shapley Interactions for Graph Neural Networks.” In The
Thirteenth International Conference on Learning Representations (ICLR), 2025.
ieee: M. Muschalik et al., “Exact Computation of Any-Order Shapley Interactions
for Graph Neural Networks,” 2025.
mla: Muschalik, Maximilian, et al. “Exact Computation of Any-Order Shapley Interactions
for Graph Neural Networks.” The Thirteenth International Conference on Learning
Representations (ICLR), 2025.
short: 'M. Muschalik, F. Fumagalli, P. Frazzetto, J. Strotherm, L. Hermes, A. Sperduti,
E. Hüllermeier, B. Hammer, in: The Thirteenth International Conference on Learning
Representations (ICLR), 2025.'
date_created: 2025-09-11T15:44:54Z
date_updated: 2025-09-11T16:14:54Z
department:
- _id: '660'
language:
- iso: eng
project:
- _id: '117'
name: TRR 318 - Project Area C
- _id: '126'
name: TRR 318 - Subproject C3
- _id: '109'
name: 'TRR 318: Erklärbarkeit konstruieren'
publication: The Thirteenth International Conference on Learning Representations (ICLR)
status: public
title: Exact Computation of Any-Order Shapley Interactions for Graph Neural Networks
type: conference
user_id: '93420'
year: '2025'
...
---
_id: '61232'
author:
- first_name: Roel
full_name: Visser, Roel
last_name: Visser
- first_name: Fabian
full_name: Fumagalli, Fabian
last_name: Fumagalli
- first_name: Eyke
full_name: Hüllermeier, Eyke
last_name: Hüllermeier
- first_name: Barbara
full_name: Hammer, Barbara
last_name: Hammer
citation:
ama: 'Visser R, Fumagalli F, Hüllermeier E, Hammer B. Explaining Outliers using
Isolation Forest and Shapley Interactions. In: Proceedings of the European
Symposium on Artificial Neural Networks (ESANN). ; 2025.'
apa: Visser, R., Fumagalli, F., Hüllermeier, E., & Hammer, B. (2025). Explaining
Outliers using Isolation Forest and Shapley Interactions. Proceedings of the
European Symposium on Artificial Neural Networks (ESANN).
bibtex: '@inproceedings{Visser_Fumagalli_Hüllermeier_Hammer_2025, title={Explaining
Outliers using Isolation Forest and Shapley Interactions}, booktitle={Proceedings
of the European Symposium on Artificial Neural Networks (ESANN)}, author={Visser,
Roel and Fumagalli, Fabian and Hüllermeier, Eyke and Hammer, Barbara}, year={2025}
}'
chicago: Visser, Roel, Fabian Fumagalli, Eyke Hüllermeier, and Barbara Hammer. “Explaining
Outliers Using Isolation Forest and Shapley Interactions.” In Proceedings of
the European Symposium on Artificial Neural Networks (ESANN), 2025.
ieee: R. Visser, F. Fumagalli, E. Hüllermeier, and B. Hammer, “Explaining Outliers
using Isolation Forest and Shapley Interactions,” 2025.
mla: Visser, Roel, et al. “Explaining Outliers Using Isolation Forest and Shapley
Interactions.” Proceedings of the European Symposium on Artificial Neural Networks
(ESANN), 2025.
short: 'R. Visser, F. Fumagalli, E. Hüllermeier, B. Hammer, in: Proceedings of the
European Symposium on Artificial Neural Networks (ESANN), 2025.'
date_created: 2025-09-11T15:53:02Z
date_updated: 2025-09-11T15:56:22Z
department:
- _id: '660'
keyword:
- FF
language:
- iso: eng
project:
- _id: '117'
name: TRR 318 - Project Area C
- _id: '126'
name: TRR 318 - Subproject C3
- _id: '109'
name: 'TRR 318: Erklärbarkeit konstruieren'
- _id: '124'
name: 'TRR 318 ; TP C01: Gesundes Misstrauen in Erklärungen'
publication: Proceedings of the European Symposium on Artificial Neural Networks (ESANN)
status: public
title: Explaining Outliers using Isolation Forest and Shapley Interactions
type: conference
user_id: '93420'
year: '2025'
...
---
_id: '61231'
author:
- first_name: Fabian
full_name: Fumagalli, Fabian
last_name: Fumagalli
- first_name: Maximilian
full_name: Muschalik, Maximilian
last_name: Muschalik
- first_name: Eyke
full_name: Hüllermeier, Eyke
last_name: Hüllermeier
- first_name: Barbara
full_name: Hammer, Barbara
last_name: Hammer
- first_name: Julia
full_name: Herbinger, Julia
last_name: Herbinger
citation:
ama: 'Fumagalli F, Muschalik M, Hüllermeier E, Hammer B, Herbinger J. Unifying Feature-Based
Explanations with Functional ANOVA and Cooperative Game Theory. In: Proceedings
of The 28th International Conference on Artificial Intelligence and Statistics
(AISTATS). Vol 258. Proceedings of Machine Learning Research. PMLR; 2025:5140-5148.'
apa: Fumagalli, F., Muschalik, M., Hüllermeier, E., Hammer, B., & Herbinger,
J. (2025). Unifying Feature-Based Explanations with Functional ANOVA and Cooperative
Game Theory. Proceedings of The 28th International Conference on Artificial
Intelligence and Statistics (AISTATS), 258, 5140–5148.
bibtex: '@inproceedings{Fumagalli_Muschalik_Hüllermeier_Hammer_Herbinger_2025, series={Proceedings
of Machine Learning Research}, title={Unifying Feature-Based Explanations with
Functional ANOVA and Cooperative Game Theory}, volume={258}, booktitle={Proceedings
of The 28th International Conference on Artificial Intelligence and Statistics
(AISTATS)}, publisher={PMLR}, author={Fumagalli, Fabian and Muschalik, Maximilian
and Hüllermeier, Eyke and Hammer, Barbara and Herbinger, Julia}, year={2025},
pages={5140–5148}, collection={Proceedings of Machine Learning Research} }'
chicago: Fumagalli, Fabian, Maximilian Muschalik, Eyke Hüllermeier, Barbara Hammer,
and Julia Herbinger. “Unifying Feature-Based Explanations with Functional ANOVA
and Cooperative Game Theory.” In Proceedings of The 28th International Conference
on Artificial Intelligence and Statistics (AISTATS), 258:5140–48. Proceedings
of Machine Learning Research. PMLR, 2025.
ieee: F. Fumagalli, M. Muschalik, E. Hüllermeier, B. Hammer, and J. Herbinger, “Unifying
Feature-Based Explanations with Functional ANOVA and Cooperative Game Theory,”
in Proceedings of The 28th International Conference on Artificial Intelligence
and Statistics (AISTATS), 2025, vol. 258, pp. 5140–5148.
mla: Fumagalli, Fabian, et al. “Unifying Feature-Based Explanations with Functional
ANOVA and Cooperative Game Theory.” Proceedings of The 28th International Conference
on Artificial Intelligence and Statistics (AISTATS), vol. 258, PMLR, 2025,
pp. 5140–48.
short: 'F. Fumagalli, M. Muschalik, E. Hüllermeier, B. Hammer, J. Herbinger, in:
Proceedings of The 28th International Conference on Artificial Intelligence and
Statistics (AISTATS), PMLR, 2025, pp. 5140–5148.'
date_created: 2025-09-11T15:48:55Z
date_updated: 2025-09-11T16:24:33Z
department:
- _id: '660'
intvolume: ' 258'
language:
- iso: eng
page: 5140-5148
project:
- _id: '117'
name: TRR 318 - Project Area C
- _id: '126'
name: TRR 318 - Subproject C3
- _id: '109'
name: 'TRR 318: Erklärbarkeit konstruieren'
publication: Proceedings of The 28th International Conference on Artificial Intelligence
and Statistics (AISTATS)
publisher: PMLR
series_title: Proceedings of Machine Learning Research
status: public
title: Unifying Feature-Based Explanations with Functional ANOVA and Cooperative Game
Theory
type: conference
user_id: '93420'
volume: 258
year: '2025'
...
---
_id: '54667'
author:
- first_name: Christian
full_name: Schulz, Christian
id: '72684'
last_name: Schulz
citation:
ama: 'Schulz C. On “Super Likes” and Algorithmic (In)Visibilities: Frictions Between
Social and Economic Logics in the Context of Social Media Platforms. Digital
Culture & Society . 2025;2/2023:45-68. doi:https://doi.org/10.14361/dcs-2023-0204'
apa: 'Schulz, C. (2025). On “Super Likes” and Algorithmic (In)Visibilities: Frictions
Between Social and Economic Logics in the Context of Social Media Platforms. Digital
Culture & Society , 2/2023, 45–68. https://doi.org/10.14361/dcs-2023-0204'
bibtex: '@article{Schulz_2025, title={On “Super Likes” and Algorithmic (In)Visibilities:
Frictions Between Social and Economic Logics in the Context of Social Media Platforms},
volume={2/2023}, DOI={https://doi.org/10.14361/dcs-2023-0204},
journal={Digital Culture & Society }, author={Schulz, Christian}, year={2025},
pages={45–68} }'
chicago: 'Schulz, Christian. “On ‘Super Likes’ and Algorithmic (In)Visibilities:
Frictions Between Social and Economic Logics in the Context of Social Media Platforms.”
Digital Culture & Society 2/2023 (2025): 45–68. https://doi.org/10.14361/dcs-2023-0204.'
ieee: 'C. Schulz, “On ‘Super Likes’ and Algorithmic (In)Visibilities: Frictions
Between Social and Economic Logics in the Context of Social Media Platforms,”
Digital Culture & Society , vol. 2/2023, pp. 45–68, 2025, doi: https://doi.org/10.14361/dcs-2023-0204.'
mla: 'Schulz, Christian. “On ‘Super Likes’ and Algorithmic (In)Visibilities: Frictions
Between Social and Economic Logics in the Context of Social Media Platforms.”
Digital Culture & Society , vol. 2/2023, 2025, pp. 45–68, doi:https://doi.org/10.14361/dcs-2023-0204.'
short: C. Schulz, Digital Culture & Society 2/2023 (2025) 45–68.
date_created: 2024-06-10T09:03:57Z
date_updated: 2025-08-15T14:06:32Z
doi: https://doi.org/10.14361/dcs-2023-0204
language:
- iso: eng
page: 45-68
project:
- _id: '109'
name: 'TRR 318: TRR 318 - Erklärbarkeit konstruieren'
publication: 'Digital Culture & Society '
publication_identifier:
isbn:
- 978-3-8376-6358-7
publication_status: published
status: public
title: 'On "Super Likes" and Algorithmic (In)Visibilities: Frictions Between Social
and Economic Logics in the Context of Social Media Platforms'
type: journal_article
user_id: '72684'
volume: 2/2023
year: '2025'
...
---
_id: '51745'
author:
- first_name: Christian
full_name: Schulz, Christian
id: '72684'
last_name: Schulz
citation:
ama: 'Schulz C. Vernakulärer Code oder die Geister, die der Algorithmus rief - digitale
Schriftlichkeit im Kontext von sozialen Medienplattformen. In: Bartelmus M, Nebrig
A, eds. Digitale Schriftlichkeit – Progammieren, Prozessieren und Codieren
von Schrift. 1st ed. transcript ; 2024. doi:https://doi.org/10.1515/9783839468135-009'
apa: Schulz, C. (2024). Vernakulärer Code oder die Geister, die der Algorithmus
rief - digitale Schriftlichkeit im Kontext von sozialen Medienplattformen. In
M. Bartelmus & A. Nebrig (Eds.), Digitale Schriftlichkeit – Progammieren,
Prozessieren und Codieren von Schrift (1st ed.). transcript . https://doi.org/10.1515/9783839468135-009
bibtex: '@inbook{Schulz_2024, place={Bielefeld}, edition={1}, title={Vernakulärer
Code oder die Geister, die der Algorithmus rief - digitale Schriftlichkeit im
Kontext von sozialen Medienplattformen}, DOI={https://doi.org/10.1515/9783839468135-009},
booktitle={Digitale Schriftlichkeit – Progammieren, Prozessieren und Codieren
von Schrift}, publisher={transcript }, author={Schulz, Christian}, editor={Bartelmus,
Martin and Nebrig, Alexander}, year={2024} }'
chicago: 'Schulz, Christian. “Vernakulärer Code oder die Geister, die der Algorithmus
rief - digitale Schriftlichkeit im Kontext von sozialen Medienplattformen.” In
Digitale Schriftlichkeit – Progammieren, Prozessieren und Codieren von Schrift,
edited by Martin Bartelmus and Alexander Nebrig, 1st ed. Bielefeld: transcript
, 2024. https://doi.org/10.1515/9783839468135-009.'
ieee: 'C. Schulz, “Vernakulärer Code oder die Geister, die der Algorithmus rief
- digitale Schriftlichkeit im Kontext von sozialen Medienplattformen,” in Digitale
Schriftlichkeit – Progammieren, Prozessieren und Codieren von Schrift, 1st
ed., M. Bartelmus and A. Nebrig, Eds. Bielefeld: transcript , 2024.'
mla: Schulz, Christian. “Vernakulärer Code oder die Geister, die der Algorithmus
rief - digitale Schriftlichkeit im Kontext von sozialen Medienplattformen.” Digitale
Schriftlichkeit – Progammieren, Prozessieren und Codieren von Schrift, edited
by Martin Bartelmus and Alexander Nebrig, 1st ed., transcript , 2024, doi:https://doi.org/10.1515/9783839468135-009.
short: 'C. Schulz, in: M. Bartelmus, A. Nebrig (Eds.), Digitale Schriftlichkeit
– Progammieren, Prozessieren und Codieren von Schrift, 1st ed., transcript , Bielefeld,
2024.'
date_created: 2024-02-22T14:12:56Z
date_updated: 2024-07-02T06:14:02Z
department:
- _id: '36'
doi: https://doi.org/10.1515/9783839468135-009
edition: '1'
editor:
- first_name: 'Martin '
full_name: 'Bartelmus, Martin '
last_name: Bartelmus
- first_name: Alexander
full_name: Nebrig, Alexander
last_name: Nebrig
language:
- iso: ger
place: Bielefeld
project:
- _id: '109'
grant_number: '438445824'
name: 'TRR 318: TRR 318 - Erklärbarkeit konstruieren'
publication: Digitale Schriftlichkeit – Progammieren, Prozessieren und Codieren von
Schrift
publication_status: published
publisher: 'transcript '
status: public
title: Vernakulärer Code oder die Geister, die der Algorithmus rief - digitale Schriftlichkeit
im Kontext von sozialen Medienplattformen
type: book_chapter
user_id: '72684'
year: '2024'
...
---
_id: '51746'
author:
- first_name: Christian
full_name: Schulz, Christian
id: '72684'
last_name: Schulz
citation:
ama: 'Schulz C. Vom foto-sozialen Graph zum Story-Format: Über die Institutionalisierung
sozialmedialer Infrastruktur aus dem Geiste der Fotografie. In: Schürmann A, Yacavone
K, eds. Die Fotografie und ihre Institutionen. Von der Lehrsammlung zum Bundesinstitut
. 1st ed. Reimer Verlag; 2024. doi:doi.org/10.5771/9783496030980'
apa: 'Schulz, C. (2024). Vom foto-sozialen Graph zum Story-Format: Über die Institutionalisierung
sozialmedialer Infrastruktur aus dem Geiste der Fotografie. In A. Schürmann &
K. Yacavone (Eds.), Die Fotografie und ihre Institutionen. Von der Lehrsammlung
zum Bundesinstitut (1st ed.). Reimer Verlag. https://doi.org/doi.org/10.5771/9783496030980'
bibtex: '@inbook{Schulz_2024, place={Berlin }, edition={1}, title={Vom foto-sozialen
Graph zum Story-Format: Über die Institutionalisierung sozialmedialer Infrastruktur
aus dem Geiste der Fotografie}, DOI={doi.org/10.5771/9783496030980},
booktitle={Die Fotografie und ihre Institutionen. Von der Lehrsammlung zum Bundesinstitut
}, publisher={Reimer Verlag}, author={Schulz, Christian}, editor={Schürmann, Anja and
Yacavone, Kathrin }, year={2024} }'
chicago: 'Schulz, Christian. “Vom foto-sozialen Graph zum Story-Format: Über die
Institutionalisierung sozialmedialer Infrastruktur aus dem Geiste der Fotografie.”
In Die Fotografie und ihre Institutionen. Von der Lehrsammlung zum Bundesinstitut
, edited by Anja Schürmann and Kathrin Yacavone, 1st ed. Berlin : Reimer
Verlag, 2024. https://doi.org/doi.org/10.5771/9783496030980.'
ieee: 'C. Schulz, “Vom foto-sozialen Graph zum Story-Format: Über die Institutionalisierung
sozialmedialer Infrastruktur aus dem Geiste der Fotografie,” in Die Fotografie
und ihre Institutionen. Von der Lehrsammlung zum Bundesinstitut , 1st ed.,
A. Schürmann and K. Yacavone, Eds. Berlin : Reimer Verlag, 2024.'
mla: 'Schulz, Christian. “Vom foto-sozialen Graph zum Story-Format: Über die Institutionalisierung
sozialmedialer Infrastruktur aus dem Geiste der Fotografie.” Die Fotografie
und ihre Institutionen. Von der Lehrsammlung zum Bundesinstitut , edited by
Anja Schürmann and Kathrin Yacavone, 1st ed., Reimer Verlag, 2024, doi:doi.org/10.5771/9783496030980.'
short: 'C. Schulz, in: A. Schürmann, K. Yacavone (Eds.), Die Fotografie und ihre
Institutionen. Von der Lehrsammlung zum Bundesinstitut , 1st ed., Reimer Verlag,
Berlin , 2024.'
date_created: 2024-02-22T14:16:53Z
date_updated: 2025-05-19T07:20:27Z
department:
- _id: '36'
doi: doi.org/10.5771/9783496030980
edition: '1'
editor:
- first_name: 'Anja '
full_name: 'Schürmann, Anja '
last_name: Schürmann
- first_name: 'Kathrin '
full_name: 'Yacavone, Kathrin '
last_name: Yacavone
language:
- iso: ger
place: 'Berlin '
project:
- _id: '109'
grant_number: '438445824'
name: 'TRR 318: TRR 318 - Erklärbarkeit konstruieren'
publication: 'Die Fotografie und ihre Institutionen. Von der Lehrsammlung zum Bundesinstitut '
publication_status: published
publisher: Reimer Verlag
status: public
title: 'Vom foto-sozialen Graph zum Story-Format: Über die Institutionalisierung sozialmedialer
Infrastruktur aus dem Geiste der Fotografie'
type: book_chapter
user_id: '72684'
year: '2024'
...
---
_id: '58224'
author:
- first_name: Philip
full_name: Kenneweg, Philip
last_name: Kenneweg
- first_name: Tristan
full_name: Kenneweg, Tristan
last_name: Kenneweg
- first_name: Fabian
full_name: Fumagalli, Fabian
last_name: Fumagalli
- first_name: Barbara
full_name: Hammer, Barbara
last_name: Hammer
citation:
ama: 'Kenneweg P, Kenneweg T, Fumagalli F, Hammer B. No learning rates needed: Introducing
SALSA - Stable Armijo Line Search Adaptation. In: 2024 International Joint
Conference on Neural Networks (IJCNN). ; 2024:1-8. doi:10.1109/IJCNN60899.2024.10650124'
apa: 'Kenneweg, P., Kenneweg, T., Fumagalli, F., & Hammer, B. (2024). No learning
rates needed: Introducing SALSA - Stable Armijo Line Search Adaptation. 2024
International Joint Conference on Neural Networks (IJCNN), 1–8. https://doi.org/10.1109/IJCNN60899.2024.10650124'
bibtex: '@inproceedings{Kenneweg_Kenneweg_Fumagalli_Hammer_2024, title={No learning
rates needed: Introducing SALSA - Stable Armijo Line Search Adaptation}, DOI={10.1109/IJCNN60899.2024.10650124},
booktitle={2024 International Joint Conference on Neural Networks (IJCNN)}, author={Kenneweg,
Philip and Kenneweg, Tristan and Fumagalli, Fabian and Hammer, Barbara}, year={2024},
pages={1–8} }'
chicago: 'Kenneweg, Philip, Tristan Kenneweg, Fabian Fumagalli, and Barbara Hammer.
“No Learning Rates Needed: Introducing SALSA - Stable Armijo Line Search Adaptation.”
In 2024 International Joint Conference on Neural Networks (IJCNN), 1–8,
2024. https://doi.org/10.1109/IJCNN60899.2024.10650124.'
ieee: 'P. Kenneweg, T. Kenneweg, F. Fumagalli, and B. Hammer, “No learning rates
needed: Introducing SALSA - Stable Armijo Line Search Adaptation,” in 2024
International Joint Conference on Neural Networks (IJCNN), 2024, pp. 1–8,
doi: 10.1109/IJCNN60899.2024.10650124.'
mla: 'Kenneweg, Philip, et al. “No Learning Rates Needed: Introducing SALSA - Stable
Armijo Line Search Adaptation.” 2024 International Joint Conference on Neural
Networks (IJCNN), 2024, pp. 1–8, doi:10.1109/IJCNN60899.2024.10650124.'
short: 'P. Kenneweg, T. Kenneweg, F. Fumagalli, B. Hammer, in: 2024 International
Joint Conference on Neural Networks (IJCNN), 2024, pp. 1–8.'
date_created: 2025-01-16T16:21:28Z
date_updated: 2025-09-11T15:37:42Z
department:
- _id: '660'
doi: 10.1109/IJCNN60899.2024.10650124
keyword:
- Training
- Schedules
- Codes
- Search methods
- Source coding
- Computer architecture
- Transformers
language:
- iso: eng
page: 1-8
project:
- _id: '109'
name: 'TRR 318: TRR 318 - Erklärbarkeit konstruieren'
- _id: '117'
name: 'TRR 318 - C: TRR 318 - Project Area C'
- _id: '126'
name: 'TRR 318 - C3: TRR 318 - Subproject C3'
publication: 2024 International Joint Conference on Neural Networks (IJCNN)
status: public
title: 'No learning rates needed: Introducing SALSA - Stable Armijo Line Search Adaptation'
type: conference
user_id: '93420'
year: '2024'
...
---
_id: '53073'
abstract:
- lang: eng
text: While shallow decision trees may be interpretable, larger ensemble models
like gradient-boosted trees, which often set the state of the art in machine learning
problems involving tabular data, still remain black box models. As a remedy, the
Shapley value (SV) is a well-known concept in explainable artificial intelligence
(XAI) research for quantifying additive feature attributions of predictions. The
model-specific TreeSHAP methodology solves the exponential complexity for retrieving
exact SVs from tree-based models. Expanding beyond individual feature attribution,
Shapley interactions reveal the impact of intricate feature interactions of any
order. In this work, we present TreeSHAP-IQ, an efficient method to compute any-order
additive Shapley interactions for predictions of tree-based models. TreeSHAP-IQ
is supported by a mathematical framework that exploits polynomial arithmetic to
compute the interaction scores in a single recursive traversal of the tree, akin
to Linear TreeSHAP. We apply TreeSHAP-IQ on state-of-the-art tree ensembles and
explore interactions on well-established benchmark datasets.
author:
- first_name: Maximilian
full_name: Muschalik, Maximilian
last_name: Muschalik
- first_name: Fabian
full_name: Fumagalli, Fabian
id: '93420'
last_name: Fumagalli
- first_name: Barbara
full_name: Hammer, Barbara
last_name: Hammer
- first_name: Eyke
full_name: Huellermeier, Eyke
id: '48129'
last_name: Huellermeier
citation:
ama: 'Muschalik M, Fumagalli F, Hammer B, Huellermeier E. Beyond TreeSHAP: Efficient
Computation of Any-Order Shapley Interactions for Tree Ensembles. In: Proceedings
of the AAAI Conference on Artificial Intelligence (AAAI). Vol 38. ; 2024:14388-14396.
doi:10.1609/aaai.v38i13.29352'
apa: 'Muschalik, M., Fumagalli, F., Hammer, B., & Huellermeier, E. (2024). Beyond
TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles.
Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 38(13),
14388–14396. https://doi.org/10.1609/aaai.v38i13.29352'
bibtex: '@inproceedings{Muschalik_Fumagalli_Hammer_Huellermeier_2024, title={Beyond
TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles},
volume={38}, DOI={10.1609/aaai.v38i13.29352},
number={13}, booktitle={Proceedings of the AAAI Conference on Artificial Intelligence
(AAAI)}, author={Muschalik, Maximilian and Fumagalli, Fabian and Hammer, Barbara
and Huellermeier, Eyke}, year={2024}, pages={14388–14396} }'
chicago: 'Muschalik, Maximilian, Fabian Fumagalli, Barbara Hammer, and Eyke Huellermeier.
“Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for
Tree Ensembles.” In Proceedings of the AAAI Conference on Artificial Intelligence
(AAAI), 38:14388–96, 2024. https://doi.org/10.1609/aaai.v38i13.29352.'
ieee: 'M. Muschalik, F. Fumagalli, B. Hammer, and E. Huellermeier, “Beyond TreeSHAP:
Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles,” in
Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024,
vol. 38, no. 13, pp. 14388–14396, doi: 10.1609/aaai.v38i13.29352.'
mla: 'Muschalik, Maximilian, et al. “Beyond TreeSHAP: Efficient Computation of Any-Order
Shapley Interactions for Tree Ensembles.” Proceedings of the AAAI Conference
on Artificial Intelligence (AAAI), vol. 38, no. 13, 2024, pp. 14388–96, doi:10.1609/aaai.v38i13.29352.'
short: 'M. Muschalik, F. Fumagalli, B. Hammer, E. Huellermeier, in: Proceedings
of the AAAI Conference on Artificial Intelligence (AAAI), 2024, pp. 14388–14396.'
date_created: 2024-03-27T14:50:04Z
date_updated: 2025-09-11T16:20:11Z
department:
- _id: '660'
doi: 10.1609/aaai.v38i13.29352
intvolume: ' 38'
issue: '13'
keyword:
- Explainable Artificial Intelligence
language:
- iso: eng
page: 14388-14396
project:
- _id: '126'
name: 'TRR 318 - C3: TRR 318 - Subproject C3'
- _id: '109'
name: 'TRR 318: TRR 318 - Erklärbarkeit konstruieren'
- _id: '117'
name: 'TRR 318 - C: TRR 318 - Project Area C'
publication: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)
publication_identifier:
issn:
- 2374-3468
- 2159-5399
publication_status: published
status: public
title: 'Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for
Tree Ensembles'
type: conference
user_id: '93420'
volume: 38
year: '2024'
...
---
_id: '55311'
abstract:
- lang: eng
text: Addressing the limitations of individual attribution scores via the Shapley
value (SV), the field of explainable AI (XAI) has recently explored intricate
interactions of features or data points. In particular, extensions of the SV,
such as the Shapley Interaction Index (SII), have been proposed as a measure to
still benefit from the axiomatic basis of the SV. However, similar to the SV,
their exact computation remains computationally prohibitive. Hence, we propose
with SVARM-IQ a sampling-based approach to efficiently approximate Shapley-based
interaction indices of any order. SVARM-IQ can be applied to a broad class of
interaction indices, including the SII, by leveraging a novel stratified representation.
We provide non-asymptotic theoretical guarantees on its approximation quality
and empirically demonstrate that SVARM-IQ achieves state-of-the-art estimation
results in practical XAI scenarios on different model classes and application
domains.
author:
- first_name: Patrick
full_name: Kolpaczki, Patrick
last_name: Kolpaczki
- first_name: Maximilian
full_name: Muschalik, Maximilian
last_name: Muschalik
- first_name: Fabian
full_name: Fumagalli, Fabian
id: '93420'
last_name: Fumagalli
- first_name: Barbara
full_name: Hammer, Barbara
last_name: Hammer
- first_name: Eyke
full_name: Huellermeier, Eyke
id: '48129'
last_name: Huellermeier
citation:
ama: 'Kolpaczki P, Muschalik M, Fumagalli F, Hammer B, Huellermeier E. SVARM-IQ:
Efficient Approximation of Any-order Shapley Interactions through Stratification.
In: Proceedings of The 27th International Conference on Artificial Intelligence
and Statistics (AISTATS). Vol 238. Proceedings of Machine Learning Research.
PMLR; 2024:3520–3528.'
apa: 'Kolpaczki, P., Muschalik, M., Fumagalli, F., Hammer, B., & Huellermeier,
E. (2024). SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions
through Stratification. Proceedings of The 27th International Conference on
Artificial Intelligence and Statistics (AISTATS), 238, 3520–3528.'
bibtex: '@inproceedings{Kolpaczki_Muschalik_Fumagalli_Hammer_Huellermeier_2024,
series={Proceedings of Machine Learning Research}, title={SVARM-IQ: Efficient
Approximation of Any-order Shapley Interactions through Stratification}, volume={238},
booktitle={Proceedings of The 27th International Conference on Artificial Intelligence
and Statistics (AISTATS)}, publisher={PMLR}, author={Kolpaczki, Patrick and Muschalik,
Maximilian and Fumagalli, Fabian and Hammer, Barbara and Huellermeier, Eyke},
year={2024}, pages={3520–3528}, collection={Proceedings of Machine Learning Research}
}'
chicago: 'Kolpaczki, Patrick, Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer,
and Eyke Huellermeier. “SVARM-IQ: Efficient Approximation of Any-Order Shapley
Interactions through Stratification.” In Proceedings of The 27th International
Conference on Artificial Intelligence and Statistics (AISTATS), 238:3520–3528.
Proceedings of Machine Learning Research. PMLR, 2024.'
ieee: 'P. Kolpaczki, M. Muschalik, F. Fumagalli, B. Hammer, and E. Huellermeier,
“SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification,”
in Proceedings of The 27th International Conference on Artificial Intelligence
and Statistics (AISTATS), 2024, vol. 238, pp. 3520–3528.'
mla: 'Kolpaczki, Patrick, et al. “SVARM-IQ: Efficient Approximation of Any-Order
Shapley Interactions through Stratification.” Proceedings of The 27th International
Conference on Artificial Intelligence and Statistics (AISTATS), vol. 238,
PMLR, 2024, pp. 3520–3528.'
short: 'P. Kolpaczki, M. Muschalik, F. Fumagalli, B. Hammer, E. Huellermeier, in:
Proceedings of The 27th International Conference on Artificial Intelligence and
Statistics (AISTATS), PMLR, 2024, pp. 3520–3528.'
date_created: 2024-07-18T09:39:14Z
date_updated: 2025-09-11T16:22:30Z
department:
- _id: '660'
intvolume: ' 238'
language:
- iso: eng
page: 3520–3528
project:
- _id: '109'
name: 'TRR 318: TRR 318 - Erklärbarkeit konstruieren'
- _id: '117'
name: 'TRR 318 - C: TRR 318 - Project Area C'
- _id: '126'
name: 'TRR 318 - C3: TRR 318 - Subproject C3'
publication: Proceedings of The 27th International Conference on Artificial Intelligence
and Statistics (AISTATS)
publisher: PMLR
series_title: Proceedings of Machine Learning Research
status: public
title: 'SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through
Stratification'
type: conference
user_id: '93420'
volume: 238
year: '2024'
...
---
_id: '58223'
abstract:
- lang: eng
text: The Shapley value (SV) is a prevalent approach of allocating credit to machine
learning (ML) entities to understand black box ML models. Enriching such interpretations
with higher-order interactions is inevitable for complex systems, where the Shapley
Interaction Index (SII) is a direct axiomatic extension of the SV. While it is
well-known that the SV yields an optimal approximation of any game via a weighted
least square (WLS) objective, an extension of this result to SII has been a long-standing
open problem, which even led to the proposal of an alternative index. In this
work, we characterize higher-order SII as a solution to a WLS problem, which constructs
an optimal approximation via SII and k-Shapley values (k-SII). We prove this representation
for the SV and pairwise SII and give empirically validated conjectures for higher
orders. As a result, we propose KernelSHAP-IQ, a direct extension of KernelSHAP
for SII, and demonstrate state-of-the-art performance for feature interactions.
author:
- first_name: Fabian
full_name: Fumagalli, Fabian
last_name: Fumagalli
- first_name: Maximilian
full_name: Muschalik, Maximilian
last_name: Muschalik
- first_name: Patrick
full_name: Kolpaczki, Patrick
last_name: Kolpaczki
- first_name: Eyke
full_name: Hüllermeier, Eyke
last_name: Hüllermeier
- first_name: Barbara
full_name: Hammer, Barbara
last_name: Hammer
citation:
ama: 'Fumagalli F, Muschalik M, Kolpaczki P, Hüllermeier E, Hammer B. KernelSHAP-IQ:
Weighted Least Square Optimization for Shapley Interactions. In: Proceedings
of the 41st International Conference on Machine Learning (ICML). Vol 235.
Proceedings of Machine Learning Research. PMLR; 2024:14308–14342.'
apa: 'Fumagalli, F., Muschalik, M., Kolpaczki, P., Hüllermeier, E., & Hammer,
B. (2024). KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions.
Proceedings of the 41st International Conference on Machine Learning (ICML),
235, 14308–14342.'
bibtex: '@inproceedings{Fumagalli_Muschalik_Kolpaczki_Hüllermeier_Hammer_2024, series={Proceedings
of Machine Learning Research}, title={KernelSHAP-IQ: Weighted Least Square Optimization
for Shapley Interactions}, volume={235}, booktitle={Proceedings of the 41st International
Conference on Machine Learning (ICML)}, publisher={PMLR}, author={Fumagalli, Fabian
and Muschalik, Maximilian and Kolpaczki, Patrick and Hüllermeier, Eyke and Hammer,
Barbara}, year={2024}, pages={14308–14342}, collection={Proceedings of Machine
Learning Research} }'
chicago: 'Fumagalli, Fabian, Maximilian Muschalik, Patrick Kolpaczki, Eyke Hüllermeier,
and Barbara Hammer. “KernelSHAP-IQ: Weighted Least Square Optimization for Shapley
Interactions.” In Proceedings of the 41st International Conference on Machine
Learning (ICML), 235:14308–14342. Proceedings of Machine Learning Research.
PMLR, 2024.'
ieee: 'F. Fumagalli, M. Muschalik, P. Kolpaczki, E. Hüllermeier, and B. Hammer,
“KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions,”
in Proceedings of the 41st International Conference on Machine Learning (ICML),
2024, vol. 235, pp. 14308–14342.'
mla: 'Fumagalli, Fabian, et al. “KernelSHAP-IQ: Weighted Least Square Optimization
for Shapley Interactions.” Proceedings of the 41st International Conference
on Machine Learning (ICML), vol. 235, PMLR, 2024, pp. 14308–14342.'
short: 'F. Fumagalli, M. Muschalik, P. Kolpaczki, E. Hüllermeier, B. Hammer, in:
Proceedings of the 41st International Conference on Machine Learning (ICML), PMLR,
2024, pp. 14308–14342.'
date_created: 2025-01-16T16:12:16Z
date_updated: 2025-09-11T16:27:05Z
department:
- _id: '660'
intvolume: ' 235'
language:
- iso: eng
page: 14308–14342
project:
- _id: '109'
name: 'TRR 318: TRR 318 - Erklärbarkeit konstruieren'
- _id: '117'
name: 'TRR 318 - C: TRR 318 - Project Area C'
- _id: '126'
name: 'TRR 318 - C3: TRR 318 - Subproject C3'
publication: Proceedings of the 41st International Conference on Machine Learning
(ICML)
publisher: PMLR
series_title: Proceedings of Machine Learning Research
status: public
title: 'KernelSHAP-IQ: Weighted Least Square Optimization for Shapley Interactions'
type: conference
user_id: '93420'
volume: 235
year: '2024'
...
---
_id: '61228'
author:
- first_name: Maximilian
full_name: Muschalik, Maximilian
last_name: Muschalik
- first_name: Hubert
full_name: Baniecki, Hubert
last_name: Baniecki
- first_name: Fabian
full_name: Fumagalli, Fabian
id: '93420'
last_name: Fumagalli
- first_name: Patrick
full_name: Kolpaczki, Patrick
last_name: Kolpaczki
- first_name: Barbara
full_name: Hammer, Barbara
last_name: Hammer
- first_name: Eyke
full_name: Huellermeier, Eyke
id: '48129'
last_name: Huellermeier
citation:
ama: 'Muschalik M, Baniecki H, Fumagalli F, Kolpaczki P, Hammer B, Huellermeier
E. shapiq: Shapley interactions for machine learning. In: Advances in Neural
Information Processing Systems (NeurIPS). Vol 37. ; 2024:130324–130357.'
apa: 'Muschalik, M., Baniecki, H., Fumagalli, F., Kolpaczki, P., Hammer, B., &
Huellermeier, E. (2024). shapiq: Shapley interactions for machine learning. Advances
in Neural Information Processing Systems (NeurIPS), 37, 130324–130357.'
bibtex: '@inproceedings{Muschalik_Baniecki_Fumagalli_Kolpaczki_Hammer_Huellermeier_2024,
title={shapiq: Shapley interactions for machine learning}, volume={37}, booktitle={Advances
in Neural Information Processing Systems (NeurIPS)}, author={Muschalik, Maximilian
and Baniecki, Hubert and Fumagalli, Fabian and Kolpaczki, Patrick and Hammer,
Barbara and Huellermeier, Eyke}, year={2024}, pages={130324–130357} }'
chicago: 'Muschalik, Maximilian, Hubert Baniecki, Fabian Fumagalli, Patrick Kolpaczki,
Barbara Hammer, and Eyke Huellermeier. “Shapiq: Shapley Interactions for Machine
Learning.” In Advances in Neural Information Processing Systems (NeurIPS),
37:130324–130357, 2024.'
ieee: 'M. Muschalik, H. Baniecki, F. Fumagalli, P. Kolpaczki, B. Hammer, and E.
Huellermeier, “shapiq: Shapley interactions for machine learning,” in Advances
in Neural Information Processing Systems (NeurIPS), 2024, vol. 37, pp. 130324–130357.'
mla: 'Muschalik, Maximilian, et al. “Shapiq: Shapley Interactions for Machine Learning.”
Advances in Neural Information Processing Systems (NeurIPS), vol. 37, 2024,
pp. 130324–130357.'
short: 'M. Muschalik, H. Baniecki, F. Fumagalli, P. Kolpaczki, B. Hammer, E. Huellermeier,
in: Advances in Neural Information Processing Systems (NeurIPS), 2024, pp. 130324–130357.'
date_created: 2025-09-11T15:39:01Z
date_updated: 2025-09-11T16:17:35Z
department:
- _id: '660'
intvolume: ' 37'
language:
- iso: eng
page: 130324–130357
project:
- _id: '117'
name: TRR 318 - Project Area C
- _id: '126'
name: TRR 318 - Subproject C3
- _id: '109'
name: 'TRR 318: Erklärbarkeit konstruieren'
publication: Advances in Neural Information Processing Systems (NeurIPS)
status: public
title: 'shapiq: Shapley interactions for machine learning'
type: conference
user_id: '93420'
volume: 37
year: '2024'
...
---
_id: '61230'
author:
- first_name: Patrick
full_name: Kolpaczki, Patrick
last_name: Kolpaczki
- first_name: Viktor
full_name: Bengs, Viktor
last_name: Bengs
- first_name: Maximilian
full_name: Muschalik, Maximilian
last_name: Muschalik
- first_name: Eyke
full_name: Hüllermeier, Eyke
last_name: Hüllermeier
citation:
ama: 'Kolpaczki P, Bengs V, Muschalik M, Hüllermeier E. Approximating the shapley
value without marginal contributions. In: Proceedings of the AAAI Conference
on Artificial Intelligence (AAAI). Vol 38. ; 2024:13246–13255.'
apa: Kolpaczki, P., Bengs, V., Muschalik, M., & Hüllermeier, E. (2024). Approximating
the shapley value without marginal contributions. Proceedings of the AAAI Conference
on Artificial Intelligence (AAAI), 38(12), 13246–13255.
bibtex: '@inproceedings{Kolpaczki_Bengs_Muschalik_Hüllermeier_2024, title={Approximating
the shapley value without marginal contributions}, volume={38}, number={12}, booktitle={Proceedings
of the AAAI conference on Artificial Intelligence (AAAI)}, author={Kolpaczki,
Patrick and Bengs, Viktor and Muschalik, Maximilian and Hüllermeier, Eyke}, year={2024},
pages={13246–13255} }'
chicago: Kolpaczki, Patrick, Viktor Bengs, Maximilian Muschalik, and Eyke Hüllermeier.
“Approximating the Shapley Value without Marginal Contributions.” In Proceedings
of the AAAI Conference on Artificial Intelligence (AAAI), 38:13246–13255,
2024.
ieee: P. Kolpaczki, V. Bengs, M. Muschalik, and E. Hüllermeier, “Approximating the
shapley value without marginal contributions,” in Proceedings of the AAAI conference
on Artificial Intelligence (AAAI), 2024, vol. 38, no. 12, pp. 13246–13255.
mla: Kolpaczki, Patrick, et al. “Approximating the Shapley Value without Marginal
Contributions.” Proceedings of the AAAI Conference on Artificial Intelligence
(AAAI), vol. 38, no. 12, 2024, pp. 13246–13255.
short: 'P. Kolpaczki, V. Bengs, M. Muschalik, E. Hüllermeier, in: Proceedings of
the AAAI Conference on Artificial Intelligence (AAAI), 2024, pp. 13246–13255.'
date_created: 2025-09-11T15:46:40Z
date_updated: 2025-09-11T16:17:54Z
department:
- _id: '660'
intvolume: ' 38'
issue: '12'
language:
- iso: eng
page: 13246–13255
project:
- _id: '117'
name: TRR 318 - Project Area C
- _id: '126'
name: TRR 318 - Subproject C3
- _id: '109'
name: 'TRR 318: Erklärbarkeit konstruieren'
publication: Proceedings of the AAAI conference on Artificial Intelligence (AAAI)
status: public
title: Approximating the shapley value without marginal contributions
type: conference
user_id: '93420'
volume: 38
year: '2024'
...