---
_id: '66885'
abstract:
- lang: eng
  text: We revisit the under-explored phenomenon of syntactic complexity convergence
    in dialogue. Extending prior topic-level analyses to full conversations, we examine
    five human-human datasets and a set of human-LLM dialogues. We integrate and evaluate
    a multidimensional set of syntactic complexity metrics to quantify structural
    variation in dialogue. Our analyses reveal robust syntactic complexity convergence
    across human-human datasets, especially in task-oriented interactions, and statistical
    tests confirm that these effects are not due to chance. In contrast, human-LLM
    dialogues show no significant convergence under individual metrics; however, linear-CKA
    uncovers a distinct cross-metric convergence pattern. Motivated by these differences,
    we use syntactic complexity as a feature for detecting LLM-involved dialogue,
    achieving 96\% accuracy. Our classification results demonstrate its potential
    without relying on likelihood-based signals such as surprisal, which require a
    language model as the estimator.
author:
- first_name: Yu
  full_name: Wang, Yu
  last_name: Wang
- first_name: Yanran
  full_name: Chen, Yanran
  last_name: Chen
- first_name: Yifan
  full_name: Wang, Yifan
  last_name: Wang
- first_name: Steffen
  full_name: Eger, Steffen
  last_name: Eger
- first_name: Hendrik
  full_name: Buschmeier, Hendrik
  id: '76456'
  last_name: Buschmeier
  orcid: 0000-0002-9613-5713
citation:
  ama: 'Wang Y, Chen Y, Wang Y, Eger S, Buschmeier H. Syntactic complexity convergence
    in dialogue: Analysis of the phenomenon and application to LLM detection. In:
    <i>Proceedings of the 2026 Conference on Empirical Methods in Natural Language
    Processing</i>. ACL.'
  apa: 'Wang, Y., Chen, Y., Wang, Y., Eger, S., &#38; Buschmeier, H. (n.d.). Syntactic
    complexity convergence in dialogue: Analysis of the phenomenon and application
    to LLM detection. <i>Proceedings of the 2026 Conference on Empirical Methods in
    Natural Language Processing</i>. 2026 Conference on Empirical Methods in Natural
    Language Processing, Budapest, Hungary.'
  bibtex: '@inproceedings{Wang_Chen_Wang_Eger_Buschmeier, place={Budapest, Hungary},
    title={Syntactic complexity convergence in dialogue: Analysis of the phenomenon
    and application to LLM detection}, booktitle={Proceedings of the 2026 Conference
    on Empirical Methods in Natural Language Processing}, publisher={ACL}, author={Wang,
    Yu and Chen, Yanran and Wang, Yifan and Eger, Steffen and Buschmeier, Hendrik}
    }'
  chicago: 'Wang, Yu, Yanran Chen, Yifan Wang, Steffen Eger, and Hendrik Buschmeier.
    “Syntactic Complexity Convergence in Dialogue: Analysis of the Phenomenon and
    Application to LLM Detection.” In <i>Proceedings of the 2026 Conference on Empirical
    Methods in Natural Language Processing</i>. Budapest, Hungary: ACL, n.d.'
  ieee: 'Y. Wang, Y. Chen, Y. Wang, S. Eger, and H. Buschmeier, “Syntactic complexity
    convergence in dialogue: Analysis of the phenomenon and application to LLM detection,”
    presented at the 2026 Conference on Empirical Methods in Natural Language Processing,
    Budapest, Hungary.'
  mla: 'Wang, Yu, et al. “Syntactic Complexity Convergence in Dialogue: Analysis of
    the Phenomenon and Application to LLM Detection.” <i>Proceedings of the 2026 Conference
    on Empirical Methods in Natural Language Processing</i>, ACL.'
  short: 'Y. Wang, Y. Chen, Y. Wang, S. Eger, H. Buschmeier, in: Proceedings of the
    2026 Conference on Empirical Methods in Natural Language Processing, ACL, Budapest,
    Hungary, n.d.'
conference:
  end_date: 2026-10-29
  location: Budapest, Hungary
  name: 2026 Conference on Empirical Methods in Natural Language Processing
  start_date: 2026-10-24
date_created: 2026-08-31T17:27:49Z
date_updated: 2026-08-31T17:33:32Z
department:
- _id: '660'
language:
- iso: eng
place: Budapest, Hungary
project:
- _id: '2752'
  name: 'TRR 318-2 - Project B07: Communicative practices of requesting information
    and explanation from LLM-based agents'
- _id: '2736'
  name: 'TRR 318-2 - Project A02: Monitoring the understanding of explanations'
publication: Proceedings of the 2026 Conference on Empirical Methods in Natural Language
  Processing
publication_status: accepted
publisher: ACL
quality_controlled: '1'
status: public
title: 'Syntactic complexity convergence in dialogue: Analysis of the phenomenon and
  application to LLM detection'
type: conference
user_id: '76456'
year: '2026'
...