Publications

Journal articles and conference papers

2 0 2 5

• On Crowdsourcing Task Design for Discourse Relation Annotation.
  Frances Yung and Vera Demberg.
  To appear in the Proceedings od the 31st International Conference on Computational Linguistics (COLING 2025).
• Implicit Discourse Relation Classification For Nigerian Pidgin.
  Muhammed Saeed, Peter Bourgonje, and Vera Demberg.
  To appear in the Proceedings od the 31st International Conference on Computational Linguistics (COLING 2025).

2 0 2 4

• Capturing variation of discourse relations in English parallel data through automatic annotation and alignment.
  Christina Pollkläsener, Frances Yung, and Ekaterina Lapshinova-Koltunski.
  In Across Languages and Cultures, 25(2), 288–309. https://doi.org/10.1556/084.2024.00903
• RSA-Control: A Pragmatics-Grounded Lightweight Controllable Text Generation Framework.
  Yifan Wang and Vera Demberg.
  In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, pp. 5561–5582, Miami, Florida, USA. Association for Computational Linguistics. https://aclanthology.org/2024.emnlp-main.318
• Generalizing across Languages and Domains for Discourse Relation Classification.
  Peter Bourgonje and Vera Demberg.
  In Proceedings of the 25th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL 2024), pages 554–565, Kyoto, Japan. Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.sigdial-1.47
• Large language models fail to derive atypicality inferences in a human-like manner.
  Charlotte Kurch, Margarita Ryzhova, and Vera Demberg.
  In Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics, pages 86–100, Bangkok, Thailand. Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.cmcl-1.8
• The Effects of Linguistic Context on Comprehension of Unknown Words.
  Margarita Ryzhova, Emilia Ellsiepen, Katharina Trinley, Iza Skrjanec, and Vera Demberg.
  Presented at the 2nd Workshop on Eye Movements and the Assessment of Reading Comprehension (2024). https://multipleye.eu/wp-content/uploads/Book_of_Abstracts24.pdf
• A Parameter-Efficient Multi-Objective Approach to Mitigate Stereotypical Bias in Language Models.
  Yifan Wang and Vera Demberg.
  In Proceedings of the 5th Workshop on Gender Bias in Natural Language Processing (GeBNLP), pages 1–19, Bangkok, Thailand. Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.gebnlp-1.1
• Human Speech Perception in Noise: Can Large Language Models Paraphrase to Improve It?
  Anupama Chingacham, Miaoran Zhang, Vera Demberg, and Dietrich Klakow.
  In Proceedings of the 1st Human-Centered Large Language Modeling Workshop, pages 1–15, TBD. ACL. https://doi.org/10.18653/v1/2024.hucllm-1.1
• Shifting Focus with HCEye: Exploring the Dynamics of Visual Highlighting and Cognitive Load on User Attention and Saliency Prediction.
  Anwesha Das, Zekun Wu, Iza Skrjanec, and Anna Maria Feit.
  In Proceedings of the ACM on Human-Computer Interaction, Volume 8, Issue ETRA. https://doi.org/10.1145/3655610
• Temperature-scaling surprisal estimates improve fit to human reading times – but does it do so for the “right reasons”?
  Tong Liu, Iza Škrjanec, and Vera Demberg.
  To appear in the Proceedings of the 2024 Annual Conference of the Association for Computational Linguistics.
  (The contribution was also presented at the ICLR 2024 Workshop on Representational Alignment as a non-archival presentation.)
• Explaining Critical Situations Over Sensor Data Streams using Proofs and Natural Language.
  Stefan Borgwardt, Vera Demberg, Mayank Jobanputra, Alisa Kovtunova, and Duy Nhu.
  In Proceedings of the 37th International Workshop on Description Logics. https://ceur-ws.org/Vol-3739/
• Do large language models and humans have similar behaviours in causal inference with script knowledge?
  Xudong Hong, Margarita Ryzhova, Daniel Adrian Biondi and Vera Demberg.
  In Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024), pages 421–437, Mexico City, Mexico. Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.starsem-1.34
• Adaptation to speakers is modulated by working memory updating and theory of mind -- a study investigating humor comprehension.
  Jia Loy and Vera Demberg.
  In Proceedings of the 45th Annual Conference of the Cognitive Science Society. https://escholarship.org/uc/item/8541n2hm
• Uniform information density explains subject doubling in French.
  Yiming Liang, Pascal Amsili, Heather Burnett, and Vera Demberg.
  In Proceedings of the 45th Annual Conference of the Cognitive Science Society. https://escholarship.org/uc/item/645673fs
• Interpreting implausible event descriptions under noise.
  Asya Achimova, Marjolein van Os, Vera Demberg, and Martin V. Butz.
  In Proceedings of the 45th Annual Conference of the Cognitive Science Society. https://escholarship.org/uc/item/13n5660h
• Capable but not cooperative? Perceptions of ChatGPT as a pragmatic speaker.
  Alexandra Mayn, Jia Loy, and Vera Demberg.
  In Proceedings of the 45th Annual Conference of the Cognitive Science Society. https://escholarship.org/uc/item/1c381535
• What processing instructions do connectives provide? Modeling the facilitative effect of the connective.
  Marian Marchal, Merel Scholman, Ted Sanders, and Vera Demberg.
  In Proceedings of the 45th Annual Conference of the Cognitive Science Society. https://escholarship.org/uc/item/2sc1k7pf
• RST-LoRA: A Discourse-Aware Low-Rank Adaptation for Long Document Abstractive Summarization.
  Dongqi Liu and Vera Demberg.
  In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), pages 2200–2220, Mexico City, Mexico. Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.naacl-long.121
• Connective Comprehension in Adults: The Influence of Lexical Transparency, Frequency, and Individual Differences.
  Merel C. J. Scholman, Marian Marchal, and Vera Demberg.
  In Discourse Processes. https://doi.org/10.1080/0163853X.2024.2325262
• SIGA: A Naturalistic NLI Dataset of English Scalar Implicatures with Gradable Adjectives.
  Rashid Nizamani, Sebastian Schuster, and Vera Demberg.
  In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 14784–14795, Torino, Italia. ELRA and ICCL. https://aclanthology.org/2024.lrec-main.1288/
• SpreadNaLa: A Naturalistic Code Generation Evaluation Dataset of Spreadsheet Formulas.
  Sebastian Schuster, Ayesha Ansar, Om Agarwal, and Vera Demberg.
  In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 15216–15225, Torino, Italia. ELRA and ICCL. https://aclanthology.org/2024.lrec-main.1323/
• Retrieval-Augmented Modular Prompt Tuning for Low-Resource Data-to-Text Generation.
  Ruitao Feng, Xudong Hong, Mayank Jobanputra, Mattes Warning, and Vera Demberg.
  In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 14053–14062, Torino, Italia. ELRA and ICCL. https://aclanthology.org/2024.lrec-main.1224/
• SciNews: From Scholarly Complexities to Public Narratives – A Dataset for Scientific News Report Generation.
  Dongqi Liu, Yifan Wang, Jia Loy, and Vera Demberg.
  In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 14429–14444, Torino, Italia. ELRA and ICCL. https://aclanthology.org/2024.lrec-main.1258/
• Modeling Orthographic Variation Improves NLP Performance for Nigerian Pidgin.
  Pin-Jie Lin, Muhammed Saeed, Merel C. J. Scholman, and Vera Demberg.
  In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 11510–11522, Torino, Italia. ELRA and ICCL. https://aclanthology.org/2024.lrec-main.1006
• DiscoGeM 2.0: A Parallel Corpus of English, German, French and Czech Implicit Discourse Relations.
  Frances Yung, Merel Scholman, Sarka Zikanova, and Vera Demberg.
  In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 4940–4956, Torino, Italia. ELRA and ICCL. https://aclanthology.org/2024.lrec-main.443
• Projecting Annotations for Discourse Relations: Connective Identification for Low-Resource Languages.
  Peter Bourgonje and Pin-Jie Lin.
  In Proceedings of the 5th Workshop on Computational Approaches to Discourse (CODI 2024), pages 39–49, St. Julians, Malta. Association for Computational Linguistics. https://aclanthology.org/2024.codi-1.4
• Prompting Implicit Discourse Relation Annotation.
  Frances Yung, Mansoor Ahmad, Merel C. J. Scholman, and Vera Demberg.
  In Proceedings of The 18th Linguistic Annotation Workshop (LAW-XVIII), pages 150–165, St. Julians, Malta. Association for Computational Linguistics. https://aclanthology.org/2024.law-1.15

2 0 2 3

• Perspective Taking Reflects Beliefs About Partner Sophistication: Modern Computer Partners Versus Basic Computer and Human Partners
  Jia E. Loy and Vera Demberg.
  In Cognitive Science, 47(12). https://doi.org/10.1111/cogs.13385
• Word Familiarity Classification From a Single Trial Based on Eye-Movements. A Study in German and English.
  Margarita Ryzhova, Iza Skrjanec, Nina Quach, Alice Virginia Chase,  Emilia Ellsiepen, and Vera Demberg.
  In Proceedings of the 2023 Symposium on Eye Tracking Research and Applications (ETRA 2023), pp. 1–2. https://doi.org/10.1145/3588015.3590118
• Exploiting Knowledge about Discourse Relations for Implicit Discourse Relation Classification.
  Nobel Varghese, Frances Yung, Kaveri Anuranjana, and Vera Demberg. 
  In Proceedings of the 4th Workshop on Computational Approaches to Discourse (CODI 2023), pp. 99-105. https://doi.org/10.18653/v1/2023.codi-1.13
• Investigating Explicitation of Discourse Connectives in Translation Using Automatic Annotations.
  Frances Yung, Merel C. J. Scholman, Ekaterina Lapshinova-Koltunski, Christina Pollkläsener, and Vera Demberg.
  In Proceedings of the 24th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDial 2023). https://aclanthology.org/2023.sigdial-1.2/
• Individual Differences in Spatial Orientation Modulate Perspective Taking in Listeners.
  Jia E. Loy and Vera Demberg.
  In Journal of Cognition, 6(1), 1–26. https://doi.org/10.5334/joc.321
• Modeling Overspecification as Uncertainty About Feature Uniqueness.
  Alexandra Mayn, Jia E. Loy, and Vera Demberg.
  Procedural and computational models of semantic and pragmatic processes (Pros&Comps Workshop 2023) .［Paper presentation］
• High Performance on a Pragmatic Task May Not Be the Result of Successful Reasoning: On the Importance of Eliciting Participants’ Reasoning Strategies
  Alexandra Mayn and Vera Demberg.
  In Journal Open Mind, 7, 156–178. https://doi.org/10.1162/opmi_a_00077
• Tackling hallucinations in neural chart summarization. 
  Islam, S. O. U., Škrjanec, I., Dušek, O., & Demberg, V. (2023, September). 
  In Proceedings of the 16th International Natural Language Generation Conference (pp. 414-423).
• ChatGPT vs Human-authored Text: Insights into Controllable Text Summarization and Sentence Style Transfer.
  Dongqi Liu and Vera Demberg.
  In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop), pages 1–18, Toronto, Canada. ACL.
• What inferences do people actually make on encountering a redundant utterance? An individual differences study.
  Margarita Ryzhova, Alexandra Mayn, and Vera Demberg.
  In Proceedings of the 45th Annual Meeting of the Cognitive Science Society (CogSci 2023). https://escholarship.org/uc/item/88g7g5z0
• Working memory updating modulates adaptation to speaker-specific use of uncertainty expressions.
  Sebastian Schuster, Alexandra Mayn, and Vera Demberg.
  In Proceedings of the 45th Annual Meeting of the Cognitive Science Society (CogSci 2023).
• Visual Coherence Loss for Coherent and Visually Grounded Story Generation.
  Xudong Hong, Vera Demberg, Asad Sayeed, Qiankun Zheng, and Bernt Schiele.
  In Proceedings of the 8th Workshop on Representation Learning for NLP (RepL4NLP 2023), pages 334–346, Toronto, Canada. ACL. https://aclanthology.org/2023.findings-acl.603/
• Low-Resource Cross-Lingual Adaptive Training for Nigerian Pidgin.
  Pin-Jie Lin, Muhammed Saeed, Ernie Chang, and Merel C. J. Scholman.
  In Proceedings of INTERSPEECH 2023, 3954-3958. https://doi.org/10.21437/Interspeech.2023-466
• Expert-adapted language models improve the fit to reading times.
  Iza Škrjanec, Frederik Yannick Broy, and Vera Demberg.
  In Procedia Computer Science. https://doi.org/10.1016/j.procs.2023.10.344
• How statistical correlations influence discourse-level processing: Clause type as a cue for discourse relations.
  Marian Marchal, Merel C. J. Scholman, and Vera Demberg.
  In Journal of Experimental Psychology: Learning, Memory, and Cognition. https://doi.org/10.1037/xlm0001270
• Revisiting Sample Size Determination in Natural Language Understanding.
  Ernie Chang, Muhammad Hassan Rashid, Pin-Jie Lin, Changsheng Zhao, Vera Demberg, Yangyang Shi, and Vikas Chandra.
  In Findings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL 2023 -- Findings).
• Incorporating Distributions of Discourse Structure for Long Document Abstractive Summarization.
  Dongqi Liu, Yifan Wang, and Vera Demberg.
  In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 5574–5590, Toronto, Canada. ACL. https://aclanthology.org/2023.acl-long.306/
• Entity Tracking in Language Models.
  Najoung Kim and Sebastian Schuster.
  In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 3835–3855, Toronto, Canada. ACL.
• Expectations over Unspoken Alternatives Predict Pragmatic Inferences.
  Jennifer Hu, Roger Levy, Judith Degen, and Sebastian Schuster.
  In Transactions of the Association for Computational Linguistics  (TACL). https://doi.org/10.1162/tacl_a_00579
• Design Choices for Crowdsourcing Implicit Discourse Relations: Revealing the Biases introduced by Task.
  Valentina Pyatkin, Frances Yung, Merel C. J. Scholman, Ido Dagan, Reut Tsarfaty, and Vera Demberg.
  In Transactions of the Association for Computational Linguistics (TACL), (2023) 11: 1014–1032.
• Visual Writing Prompts: Character-Grounded Story Generation with Curated Image Sequences.
  Xudong Hong, Asad Sayeed, Khushboo Mehra, Vera Demberg, and Bernt Schiele.
  In Transactions of the Association for Computational Linguistics (TACL). http://doi.org/10.1162/tacl_a_00553
• Expressing non-volitional causality in English.
  Jet Hoek and Merel C. J. Scholman.
  In L. Jedrzejowski & C. Fleczoreck (eds.), Micro- and Macro-variation of Causal Clauses. Synchronic and Diachronic Insights (p. 167–183). John Benjamins Publishing Company. https://doi.org/10.1075/slcs.231.06hoe
• Processing cost effects of atypicality inferences in a dual-task setup.
  Margarita Ryzhova and Vera Demberg.
  In Journal of Pragmatics, 211, 47–80. https://doi.org/10.1016/j.pragma.2023.04.005
• A systematic evaluation of factors affecting referring expression choice in passage completion tasks.
  Vera Demberg, Ekaterina Kravtchenko, and Jia Ern Loy.
  In Journal of Memory and Language, 130. https://doi.org/10.1016/j.jml.2023.104413
• A Data-driven Investigation of Noise-Adaptive Utterance Generation With Linguistic Modification.
  Anupama Chingacham, Vera Demberg, and Dietrich Klakow.
  In IEEE Spoken Language Technology Workshop (SLT) 2023. https://doi.org/10.1109/SLT54892.2023.10022437

2 0 2 2

• Advancing translational research in neuroscience through multi-task learning.
  Han Cao, Xudong Hong, Heike Tost, Andreas Meyer-Lindenberg, and Emanuel Schwarz.
  In Frontiers in Psychiatry 13 (2022). https://doi.org/10.3389/fpsyt.2022.993289
• Rational Speech Comprehension: Interaction between Predictability, Acoustic Signal, and Noise.
  Marjolein Van Os, Jutta Kray, and Vera Demberg.
  In Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2022.914239
• Pragmatic comprehension in individuals is stable across time and some tasks.
  Margarita Ryzhova, Jia Loy, and Vera Demberg.
  In Frau, F., Bischetti, L., Pompei, C., Scalingi, B., Domaneschi, F., & Bambini, V. (eds.), Book of Abstracts - XPRAG 2022. https://doi.org/10.17605/OSF.IO/C4KP2
• Right for the Wrong Reason? On the importance of eliciting participants' reasoning.
  Alexandra Mayn and Vera Demberg.
  In Frau, F., Bischetti, L., Pompei, C., Scalingi, B., Domaneschi, F., & Bambini, V. (eds.), Book of Abstracts - XPRAG 2022. https://doi.org/10.17605/OSF.IO/C4KP2
• Two-Stage Movie Scripts Summarization: An Efficient Method For Low-Resource Long Documents Summarization.
  Dongqi Liu, Xudong Hong, Pin-Jie Lin, Ernie Chang, and Vera Demberg.
  In Proceedings of The Workshop on Automatic Summarization for Creative Writing, pp. 57–66. https://aclanthology.org/2022.creativesumm-1.9
• Label distributions help implicit discourse relation classification.
  Frances Yung, Kaveri Anuranjana, Merel C. J. Scholman, and Vera Demberg.
  In Proceedings of the Third Workshop on Computational Approaches to Discourse (CODI 2022), pp. 48–53. https://aclanthology.org/2022.codi-1.7/
• Zero-Shot Script Parsing
  Fangzhou Zhai, Vera Demberg, and Alexander Koller.
  In Proceedings of the 29th International Conference on Computational Linguistics (CoLing 2022).
• Establishing Annotation Quality in Multi-Label Annotations.
  Marian Marchal, Merel C. J. Scholman, Frances Yung, and Vera Demberg.
  In Proceedings of the 29th International Conference on Computational Linguistics (CoLing 2022).
• The effect of domain knowledge and implicitation on discourse relation inferences.
  Marian Marchal, Merel C. J. Scholman, and Vera Demberg.
  In Dialogue & Discourse,13(2), pp. 49-78. https://doi.org/10.5210/dad.2022.202
• Few-Shot Pidgin Text Adaptation via Contrastive Fine-Tuning.
  Ernie Chang, Jesujoba Alabi, David Adelani, and Vera Demberg.
  In Proceedings of the 29th International Conference on Computational Linguistics (CoLing 2022).
• Programmable Annotation with Diversed Heuristics and Data Denoising.
  Ernie Chang, Alex Marin, and Vera Demberg.
  In Proceedings of the 29th International Conference on Computational Linguistics (CoLing 2022).
• Improving Zero-Shot Multilingual Text Generation via Iterative Distillation.
  Ernie Chang, Alex Marin, and Vera Demberg.
  In Proceedings of the 29th International Conference on Computational Linguistics (CoLing 2022).
• Dialogue Pidgin Text Adaptation via Contrastive Fine-Tuning.
  Ernie Chang, Jesujoba Oluwadara Alabi, David Ifeoluwa Adelani, and Vera Demberg.
  In Proceedings of 3rd Workshop on African Natural Language Processing at ICLR. April 2022.
• Predictability effects in degraded speech comprehension are reduced as a function of attention.
  Pratik Bhandari, Vera Demberg, and Jutta Kray.
  In Language and Cognition, First View, pp. 1-18. https://doi.org/10.1017/langcog.2022.16
• Discourse rules: The effects of clause order principles on the reading process.
  Merel M. J. Scholman, Liam Blything, L., Kate Cain, Jet Hoek, and Jacqueline Evers-Vermeul.
  In Language, Cognition and Neuroscience, 2022. https://doi.org/10.1080/23273798.2022.2077971
• Informationally Redundant Utterances Elicit Pragmatic Inferences.
  Ekaterina Kravtchenko and Vera Demberg.
  In Cognition, 2022. https://doi.org/10.1016/j.cognition.2022.105159
• Modeling atypicality inferences in pragmatic reasoning.
  Ekaterina Kravtchenko and Vera Demberg.
  In Proceedings of the 44th Annual Meeting of the Cognitive Science Society (CogSci 2022). https://escholarship.org/uc/item/7630p08b
• Individual Differences in a Pragmatic Reference Game.
  Alexandra Mayn and Vera Demberg.
  In Proceedings of the 44th Annual Meeting of the Cognitive Science Society (CogSci 2022). https://escholarship.org/uc/item/0hb5h0hk
• Pragmatics of Metaphor Revisited: Formalizing the Role of Typicality and Alternative Utterances in Metaphor Understanding.
  Alexandra Mayn and Vera Demberg.
  In Proceedings of the 44th Annual Meeting of the Cognitive Science Society (CogSci 2022). https://escholarship.org/uc/item/7kq207zs
• Partner effects and individual differences on perspective taking.
  Jia Loy and Vera Demberg.
  In Proceedings of the 44th Annual Meeting of the Cognitive Science Society (CogSci 2022). https://escholarship.org/uc/item/3c98b0fw
• Descriptively adequate and cognitively plausible? Validating distinctions between types of coherence relations.
  Merel C. J.  Scholman, Vera Demberg, and Ted J. M. Sanders.
  In Discours, 30, 1-30, 2022. https://doi.org/10.4000/discours.12075
• Design Choices in Crowdsourcing Discourse Relation Annotations: The Effect of Worker Selection and Training.
  Merel C. J. Scholman, Valentina Pyatkin, Frances Yung, Ido Dagan, Reut Tsarfaty, and Vera Demberg.
  In Proceedings of the 13th International Conference on Language Resources and Evaluation (LREC 22), Marseille, France.
• DiscoGeM: A Crowdsourced Corpus of Genre-Mixed Implicit Discourse Relations.
  Merel C. J. Scholman, Tianai Dong, Frances Yung, and Vera Demberg.
  In Proceedings of the 13th International Conference on Language Resources and Evaluation (LREC 22), Marseille, France.
• Barch: an English dataset of bar chart summaries.
  Iza Skrjanec, Muhammad Salman Edhi, and Vera Demberg.
  In Proceedings of the 13th International Conference on Language Resources and Evaluation (LREC 2022), Marseille, France.
• Logic-Guided Message Generation from Raw Real-Time Sensor Data.
  Ernie Chang, Alisa Kovtunova, Stefan Borgwardt, Vera Demberg, Kathryn Chapman, and Hui-Syuan Yeh.
  In Proceedings of the 13th International Conference on Language Resources and Evaluation (LREC 2022); Marseille, France, June, pages 21-23, 2022.

2 0 2 1

• Is there less agreement when the discourse is underspecified?
  Jet Hoek, Merel C. J. Scholman, and Ted J. M. Sanders.
  In Proceedings of the DiscAnn Workshop.
• A practical perspective on connective generation.
  Frances Yung, Merel C. J. Scholman, and Vera Demberg.
  In Proceedings of the Second Workshop on Computational Approaches to Discourse (CODI). https://doi.org/10.18653/v1/2021.codi-main.7
• Comparison of methods for explicit discourse connective identification across various domains.
  Merel C. J. Scholman, Tianai Dong, Frances Yung, and Vera Demberg.
  In Proceedings of the Second Workshop on Computational Approaches to Discourse (CODI). https://doi.org/10.18653/v1/2021.codi-main.9
• Semi-automatic discourse annotation in a low-resource language: Developing a connective lexicon for Nigerian Pidgin
  Marian Marchal, Merel C. J. Scholman, and Vera Demberg.
  In Proceedings of the Second Workshop on Computational Approaches to Discourse (CODI). http://doi.org/10.18653/v1/2021.codi-main.8
• Time-Aware Ancient Chinese Text Translation and Inference.
  Ernie Chang, Yow-Ting Shiue, Hui-Syuan Yeh, and Vera Demberg.
• Why Do I Have to Take Over Control? Evaluating Safe Handovers with Advance Notice and Explanations in Highly Automated Driving
  Frederik Wiehr, Anke Hirsch, Lukas Schmitz, Nina Knieriemen, Alisa Kovtunova, Stefan Borgwardt, Ernie Chang, Vera Demberg, et al.
  In Proceedings of the 23rd ACM International Conference on Multimodal Interfaces (ICMI). https://doi.org/10.1145/3462244.3479884
• Logic-Guided Neural Utterance Generation from Drone Sensory Data.
  Stefan Borgwardt, Ernie Chang, Kathryn Chapman, Vera Demberg, Alisa Kovtunova, and Hui-Syuan Yeh.
  In Proceedings of 34th International Workshop on Description Logics.
• The SelectGen Challenge: Finding the Best Training Samples for Few-Shot Neural Text Generation.
  Ernie Chang, Xiaoyu Shen, Alex Marin, and Vera Demberg.
  In Proceedings of the 14th International Conference on Natural Language Generation.
• Semantic Predictability Facilitates Comprehension of Degraded Speech in a Graded Manner.
  Pratik Bhandari, Vera Demberg, and Jutta Kray.
  In Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2021.714485
• Mishearing as a Side Effect of Rational Language Comprehension in Noise.
  Marjolein van Os, Jutta Kray, and Vera Demberg.
  In Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2021.679278
• Exploring the Potential of Lexical Paraphrases for Mitigating Noise-Induced Comprehension Errors.
  Anupama Chingacham, Vera Demberg, and Dietrich Klakow.
  In Proceedings of Interspeech 2021. https://doi.org/10.48550/arXiv.2107.08337
  Best student paper award!
• Interaction of Script Knowledge and Temporal Discourse Cues in a Visual World Study.
  Alessandra Zarcone and Vera Demberg.
  In Discourse Processes, 58(9). https://doi.org/10.1080/0163853X.2021.1930807
• On Training Instance Selection for Few-Shot Neural Text Generation.
  Ernie Chang, Xiaoyu Shen, Hui-Syuan Yeh, and Vera Demberg.
  In Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021).
• Entity Enhancement for Implicit Discourse Relation Classification in the Biomedical Domain.
  Wei Shi and Vera Demberg.
  In Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021). https://doi.org/10.18653/v1/2021.acl-short.116
• Limits to the rational production of discourse connectives.
  Frances Yung, Jana Jungbluth, and Vera Demberg.
  In Frontiers of Psychology. https://www.frontiersin.org/articles/10.3389/fpsyg.2021.660730/abstract
• A bathtub by any other name: the reduction of german compounds in predictive contexts.
  Alessandra Zarcone and Vera Demberg.
  In Proceedings of the 43rd Annual Meeting of the Cognitive Science Society (CogSci 2021).
• Recognition of minimal pairs in (un)predictive sentence contexts in two types of noise.
  Marjolein van Os, Jutta Kray, and Vera Demberg.
  In Proceedings of the 43rd Annual Meeting of the Cognitive Science Society (CogSci 2021). https://escholarship.org/uc/item/70z995v4
• The online processing of causal and concessive discourse connectives.
  Judith Köhne-Fuetterer, Heiner Drenhaus, Francesca Delogu, and Vera Demberg.
  Linguistics, 59(2), 417-448. https://doi.org/10.1515/ling-2021-0011
• The Index of Cognitive Activity Predicts Cognitive Processing Load in Linguistic Task.
  Hong Gao, Zijian Lu, Vera Demberg, and Enkelejda Kasneci.
  In Proceedings of the EMICS workshop at CHI’21.
• Does the Order of Training Samples Matter? Improving Neural Data-to-Text Generation with Curriculum Learning
  Ernie Chang, Hui-Syuan Yeh, and Vera Demberg.
  In Proceedings of the Conference of the European Chapter of the Association for Computational Linguistics (EACL 2021).
• Neural Data-to-Text Generation with LM-based Text Augmentation.
  Ernie Chang, Xiaoyu Shen, Dawei Zhu, Vera Demberg, and Hui Su.
  In Proceedings of the 2021 Conference of the European Chapter of the Association for Computational Linguistics (EACL 2021).
• Jointly Improving Language Understanding and Language Generation with Quality-Weighted Weak Supervision of Automatic Labeling
  Ernie Chang, Vera Demberg, and Alex Marin.
  In Proceedings of the 2021 Conference of the European Chapter of the Association for Computational Linguistics (EACL 2021).

2 0 2 0

• The role of non-connective discourse cues and their interaction with connectives.
  Ludivine Crible and Vera Demberg.
  In Pragmatics and Cognition,27(2), 2020.
• When Do We Leave Discourse Relations Underspecified? The Effect of Formality and Relation Type.
  Ludivine Crible and Vera Demberg.
  In Discours 26 (2020). https://doi.org/10.4000/discours.10848
• DART: A Lightweight Quality-Suggestive Data-to-Text Annotation Tool.
  Ernie Chang, Jeriah Caplinger, Alex Marin, Xiaoyu Shen, and Vera Demberg.
  In Proceedings of the 28th International Conference on Computational Linguistics (CoLing 2020) -- Demos.
  Best Demo Paper Award
• Story Generation with Rich Details.
  Fangzhou Zhai, Vera Demberg, and Alexander Koller.
  In Proceedings of the 28th International Conference on Computational Linguistics (CoLing 2020). https://doi.org/10.18653/v1/2020.coling-main.212
• Individual differences in expecting coherence relations: Exploring the variability in sensitivity to contextual signals in discourse.
  Merel C. J. Scholman, Vera Demberg, and Ted J. M. Sanders.  
  Discourse Processes, 57(10). https://doi.org/10.1080/0163853X.2020.1813492
• Diverse and Relevant Visual Storytelling with Scene Graph Embeddings.
  Xudong Hong, Rakshith Shetty, Asad Sayeed, Khushboo Mehra, Vera Demberg, and Bernt Schiele.
  In Proceedings of the 24th Conference on Computational Natural Language Learning, CoNLL 2020. https://doi.org/10.18653/v1/2020.conll-1.34
• Modeling the interplay of rational production and comprehension of ambiguous connectives.
  Frances Yung, Jana Jungbluth, and Vera Demberg.
  In Proceedings of the 53rd Annual Meeting of the Societas Linguistica Europaea (SLE).
• Processing particularized pragmatic inferences under load.
  Margarita Ryzhova and Vera Demberg. 
  In Proceedings of the 42nd Annual Meeting of the Cognitive Science Society (CogSci 2020). https://cogsci.mindmodeling.org/2020/papers/0622/0622.pdf
• Unsupervised Pidgin Text Generation By Pivoting English Data and Self-Training.
  Ernie Chang, David Ifeoluwa Adelani, Xiaoyu Shen, and Vera Demberg.
  In Proceedings of Workshop at ICLR 8th International Conference on Learning Representations (Virtual Conference, formerly at Addis Ababa, Ethiopia) April 2020.
• Interpretation of Discourse Connectives Is Probabilistic: Evidence From the study of But and Although.
  Fatemeh Torabi Asr and Vera Demberg.
  Discourse Processes, pp. 1-24, 2020, Routledge.https://doi.org/10.1080/0163853x.2019.1700760
• How speakers adapt object descriptions to listeners under load.
  Jorrig Vogels, David M. Howcroft, Elli Tourtouri, and Vera Demberg.
  Language, Cognition and Neuroscience, 35(1), pp. 1-15, 2020. https://www.tandfonline.com/doi/full/10.1080/23273798.2019.164883

2 0 1 9

• Improving Language Generation from Feature-Rich Tree-Structured Data with Relational Graph Convolutional Encoders.
  Xudong Hong, Chuan-Yi Ernie Chang, and Vera Demberg.
  In Proceedings of the Second Workshop on Multilingual Surface Realisation (MSR) at EMNLP, Hong Kong, Nov 2019, pp.75-80. https://doi.org/10.18653/v1/D19-6310
• Next Sentence Prediction helps implicit Discourse Relation Classification within and across Domains.
  Wei Shi and Vera Demberg.
  In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP/IJCNLP), Hong Kong, Nov 2019.
  https://doi.org/10.18653/v1/D19-1586
• Crowdsourcing Discourse Relation Annotations by a Two-Step Connective Insertion Task.
  Frances Yung, Merel Scholman, and Vera Demberg.
  Linguistic Annotation Workshop at ACL. LAW XIII 2019. https://doi.org/10.18653/v1/w19-4003
• How compatible are our discourse annotation frameworks? Insights from mapping RST-DT and PDTB annotations.
  Vera Demberg, Merel Scholman and Fatemeh Torabi Asr.
  Dialogue & Discourse 10 (1), 87-135. 2019.  
  (previous version: V Demberg, FT Asr, M Scholman - arXiv preprint arXiv:1704.08893, 2017)
• Verb-second effect on quantifier scope interpretation.
  Asad Sayeed, Matthias Lindemann, and Vera Demberg.
  In Proceedings of  the Workshop on Cognitive Modeling and Computational Linguistics (CMCL) 2019.
  https://doi.org/10.18653/v1/w19-2915
• Learning to Explicitate Connectives with Seq2Seq Network for Implicit Discourse Relation Classification.
  Wei Shi and Vera Demberg.
  In Proceedings of the 13th International Conference on Computational Semantics (IWCS 2019), Gothenburg, Sweden.
  https://www.aclweb.org/anthology/W19-0416.pdf
• Acquiring Annotated Data with Cross-Lingual Explicitation for Implicit Discourse Relation Classification.
  Wei Shi, Frances Yung, and Vera Demberg.
  In Proceedings of the 7th Workshop on Rhetorical Structure Theory and Related Formalsms (DISRPT@NAACL2019), Minneapolis, USA. https://doi.org/10.18653/v1/W19-2703
• Effects of aging and dual-task demands on the comprehension of less expected sentence continuations: Evidence from pupillometry.
  Katja Ingrid Häuser, Vera Demberg, and Jutta Kray.
  Frontiers in Psychology-Cognition 29 March 2019. https://doi.org/10.3389/fpsyg.2019.00709
• Cognitive Models of Syntax and Sentence Processing.
  Vera Demberg and Frank Keller.
  In P. Hagoort (Ed.), Human Language: From Genes and Brains to Behavior (pp. 293-312). MIT Press.
• A Hybrid Model for Globally Coherent Story Generation.
  Fangzhou Zhai, Vera Demberg, Pavel Shkadzko, Wei Shi, and Asad Sayeed.
  In Proceedings of the Second Workshop on Storytelling, 2019. Florence Publisher: Association for Computational Linguistics. https://doi.org/10.18653/v1/w19-3404

2 0 1 8

• Surprisal modulates dual-task performance in older adults: Pupillometry shows age-related trade-offs in task performance and the time-course of language processing. 
  Katja Häuser, Vera Demberg, and Jutta Kray.
  Psychology and Aging, 33(8), 1168-1180. https://doi.org/10.1037/pag0000316
• The Index of Cognitive Activity as a measure of cognitive processing load in dual task settings.
  Jorri Vogels, Vera Demberg, and Jutta Kray.
  Frontiers in Psychology; November 30, 2018. https://doi.org/10.3389/fpsyg.2018.02276
• Toward Bayesian Synchronous Tree Substitution Grammars for Sentence Planning.
  David M. Howcroft, Dietrich Klakow, and Vera Demberg.
  In Proceedings of the 11th International Conference on Natural Language Generation (INLG2018); Tilburg, The Netherlands; November 05-08, 2018. https://doi.org/10.18653/v1/W18-6546
• Using Universal Dependencies in cross-linguistic complexity research.
  Aleksandrs Berdicevskis, Cagri Cöltekin, Katharina Ehret, Kilu von Prince, Daniel Ross, Bill Thompson, Chunxiao Yan,  Vera Demberg, Gary Lupyan, and Taraka Rama.
  In Proceedings of the 2nd Workshop on Universal Dependencies (UDW 2018 during EMNLP2018); Brussels, Belgium; November 01, 2018. https://doi.org/10.18653/v1/W18-6002
• Do speakers produce discourse connectives rationally?
  Frances Yung and Demberg, Vera.
  In Proceedings of the 8th Workshop on Cognitive Aspects of Computational Language Learning and Processing (CogACLL2018), Melbourne, Australia, July 19, 2018. https://doi.org/10.18653/v1/w18-2802
• Learning distributed event representations with a multi-task approach.
  Xudong Hong, Asad Sayeed, and Vera Demberg.
  In Proceedings of the 7th Joint Conference on Lexical and Computational Semantics *SEM2018; New Orleans, USA; June 05-06, 2018. https://doi.org/10.18653/v1/s18-2002
• Unifying dimensions in coherence relations: How various annotation frameworks are related.
  Ted J. M. Sanders, Vera Demberg, Jet Hoek, Merel C. J. Scholman, Fatemeh Torabi Asr, Sandrine Zufferey, and Jacqueline Evers-Vermeul.
  Corpus Linguistics and Linguistic Theory. May 22, 2018. https://doi.org/10.1515/cllt-2016-0078
• Rollenwechsel-English: a large-scale semantic role corpus.
  Asad Sayeed, Pavel Shkadzko, and Vera Demberg.
  In Proceedings of the 11th International Conference on Language Resources and Evaluation (LREC 2018); Miyazaki, Japan; May 07-12, 2018. http://www.lrec-conf.org/proceedings/lrec2018/summaries/922.html
• POS tag perplexity as a measure of syntactic complexity.
  Kilu von Prince, and Vera Demberg.
  In Proceedings of the 1st Shared Task on Measuring Language Complexity Workshop; Torun, Poland; April 15, 2018. https://publikationen.sulb.uni-saarland.de/handle/20.500.11880/29760
• Improving Variational Encoder-Decoders in Dialogue Generation.
  Xiaoyu Shen, Hui Su, Shuzi Niu, and Vera Demberg.
  In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18); New Orleans, USA; February 02-07, 2018. https://doi.org/10.1609/aaai.v32i1.11960

2 0 1 7

• Using Explicit Discourse Connectives in Translation for Implicit Discourse Relation Classification.
  Wei Shi, Frances Yung, Raphael Rubino, and Vera Demberg.
  In Proceedings of the8th International Joint Conference on Natural Language Processing (IJCNLP), Taipei / Taiwan, 2017.  https://www.aclweb.org/anthology/I17-1049.pdf
• G-TUNA: a corpus of referring expressions in German, including duration information.
  David M. Howcroft, Jorrig Vogels, and Vera Demberg.
  In Proceedings of the 10th International Conference on Natural Language Generation (INLG), 2017. 10.18653/v1/W17-3522
• The Extended SPaRKy Restaurant Corpus: designing a corpus with variable information density.
  David M. Howcroft, Dietrich Klakow, and Vera Demberg.
  In Proceedings of the 18th Annual Conference of the International Speech Communication Association (INTERSPEECH), 2017. http://dx.doi.org/10.21437/Interspeech.2017-1555
• Examples and specifications that prove a point: Distinguishing between elaborative and argumentative discourse relations.
  Merel C. J. Scholman and Vera Demberg.
  Dialogue and Discourse, 2017. https://doi.org/10.5087/dad.2017.203
• 'On the one hand' as a cue to anticipate upcoming discourse structure. 
  Merel C. J. Scholman, Hannah Rohde and Vera Demberg. Journal of Memory and Language,2017. https://doi.org/10.1016/j.jml.2017.07.010
• Modeling semantic expectations: Using script knowledge for referent prediction. 
  Ashutosh Modi, Ivan Titov, Vera Demberg, Asad Sayeed, and Manfred Pinkal. Transactions of the Association for Computational Linguistics (TACL), 2017.https://doi.org/10.1162/tacl_a_00044
• Crowdsourcing discourse interpretations: On the influence of context and the reliability of a connective insertion task. 
  Merel Scholman and Vera Demberg.
  In Proceedings of the Linguistic Annotation Workshop (LAW), 2017. https://doi.org/10.18653/v1/W17-0803
• A systematic study of neural discourse models for implicit discourse relation. 
  Attapol T. Rutherford, Vera Demberg, and Nianwen Xue.In Proceedings of the European Chapter of the Association for Computational Linguistics (EACL), 2017.https://doi.org/10.18653/v1/e17-1027
• Psycholinguistic models of sentence processing improve sentence readability ranking.
  David Howcroft and Vera Demberg.
  In Proceedings of the European Chapter of the Association for Computational Linguistics (EACL), 2017. https://doi.org/10.18653/v1/e17-1090
• On the need of cross validation for discourse relation classification.
  Wei Shi and Vera Demberg.
  In Proceedings of the European Chapter of the Association for Computational Linguistics (EACL), 2017. https://doi.org/10.18653/v1/e17-2024

2 0 1 6

• From OpenCCG to AI planning: Detecting infeasible edges in sentence generation.
  Maximilian Schwenger, Alvaro Torralba, Jörg Hoffmann, David M. Howcroft, and Vera Demberg
  In Proceedings of the 26th International Conference on Computational Linguistics (Coling’16), Osaka, Japan, 2016.
• Salience and attention in surprisal-based accounts of language processing.
  Alessandra Zarcone, Marten van Schijndel, Jorrig Vogels, and Vera Demberg.
  Frontiers in Psychology, 7(844), 2016.
• The frequency of rapid pupil dilations as a measure of linguistic processing difficulty.
  Vera Demberg and Asad Sayeed.
  PLOS ONE, 11(1), 2016.
• Search challenges in natural language generation with complex optimization objectives.
  Vera Demberg, JörgHoffmann, David M.Howcroft, Dietrich Klakow, and Álvaro Torralba.
  KI - Künstliche Intelligenz, 30(1), 63–69, 2016.
• Information density and linguistic encoding (ideal). 
  Matthew W. Crocker, Vera Demberg, and Elke Teich.
  KI, 30(1), 77–81, 2016.
• Event participant modelling with neural networks.
  Ottokar Tilk, Vera Demberg, Asad B. Sayeed, Dietrich Klakow, and Stefan Thater.
  In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, EMNLP 2016, Austin, Texas, USA, November 1-4, 2016, pages 171–182, 2016.
• Annotating discourse relations in spoken language: A comparison of the PDTB and CCR frameworks.
  Ines Rehbein, Merel Scholman, and Vera Demberg.
  In Proceedings of the Tenth International Conference on Language Resources and Evaluation LREC 2016, Portoroz, Slovenia, May 23-28,2016.
• Lingoturk: managing crowdsourced tasks for psycholinguistics. 
  Florian Pusse, Asad B. Sayeed, and Vera Demberg.
  In Proceedings of the Demonstrations Session, NAACL HLT 2016, The 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, San Diego California, USA, June 12-17, 2016, pp. 57–61, 2016.
• Roleo: visualising thematic fit spaces on the web.
  Asad B. Sayeed, Xudong Hong, and Vera Demberg.
  In Proceedings of the Demonstrations Session, NAACL HLT 2016, The 2016 Conference of the North Ameri- can Chapter of the Association for Computational Linguistics: Human Language Technologies, San Diego California, USA, June 12-17, 2016.
• Improving event prediction by representing script participants. 
  Simon Ahrendt and Vera Demberg.
  In Proceedings of the 15th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, San Diego, California, 2016.

2 0 1 5

• Improving unsupervised vector-space thematic fit evaluation via role-filler prototype clustering. 
  Clayton Greenberg, Asad B. Sayeed, and Vera Demberg.
  In NAACL HLT 2015, The 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Denver, Colorado, USA, May 31 - June 5, 2015, pp. 21–31, 2015.
• Verb polysemy and frequency effects in thematic fit modeling. 
  Clayton Greenberg, Vera Demberg, and Asad B. Sayeed.
  In Proceedings of the 6th Workshop on Cognitive Modeling and Computational Linguistics (CMCL), p. 4857, Denver, Colorado, USA, 2015.
• Learning to predict script events from domain-specific text.
  Rachel Rudinger, Vera Demberg, Ashutosh Modi, Benjamin Van Durme, and Manfred Pinkal.
  In Proceedings of the Fourth Joint Conference on Lexical and Computational Semantics, *SEM 2015, June 4-5, 2015, Denver, Colorado, USA,pp. 205–210, 2015.
• Semantically underinformative utterances trigger pragmatic inferences. 
  Ekaterina Kravtchenko and Vera Demberg.
  In Proceedings of the 37th Annual Meeting of the Cognitive Science Society, CogSci 2015, Pasadena, California, USA, July 22-25, 2015, 2015.
• Towards flexible, small-domain surface generation: Combining data-driven and grammatical approaches.
  Andrea Fischer, Vera Demberg, and Dietrich Klakow.
  In ENLG 2015 - Proceedings of the 15th European Workshop on Natural Language Generation, 10-11 September 2015, University of Brighton, Brighton, UK, pp. 105–108, 2015.
• Vector-space calculation of semantic surprisal for predicting word pronunciation duration.
  Asad B. Sayeed, Stefan Fischer, and Vera Demberg.
  In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, ACL 2015, July 26-31, 2015, Beijing, China, Volume 1: Long Papers, pp. 763–773, 2015.
• Uniform information density at the level of discourse relations: Negation markers and discourse connective omission.
  Fatemeh Torabi Asr and Vera Demberg.
  In Proceedings of the 11th International Conference on Computational Semantics (IWCS), 2015.

2 0 1 4

• Combining unsupervised syntactic and semantic models of thematic fit.
  Asad Sayeed and Vera Demberg.
  In Proceedings of the First Italian Conference on Computational Linguistics (CLIC-it), 2014.
• Incremental semantic role labeling with tree adjoining grammar.
  Ioannis Konstas, Frank Keller, Vera Demberg, and Mirella Lapata.
  In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2014.
• Incremental and predictive discourse processing based on causal and concessive discourse markers: ERP studies on German and English. 
  Heiner Drenhaus, Vera Demberg, Judith Koehne, and Francesca Delogu.
  In Proceedings of the 36th Annual Meeting of the Cognitive Science Society (CogSci-14), p. 403-409; 2014.

2 0 1 3

• Incremental, predictive parsing with psycholinguistically motivated tree-adjoining grammar.
  Vera Demberg, Frank Keller, and Alexander Koller.
  Computational Linguistics,39(4), 2013.
• Measuring linguistically-induced cognitive load during driving using the contre task.
  Vera Demberg, Asad Sayeed, Angela Mahr, and Christian Müller.
  In Proceedings of the 5th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutoUI), Eindhoven, The Netherlands, 2013.
• The semantic augmentation of a psycholinguistically-motivated syntactic formalism.
  Asad Sayeed and Vera Demberg.
  In Proceedings of the Fourth Annual Workshop on Cognitive Modeling and Computational Linguistics (CMCL), pp. 57–65, Sofia, Bulgaria, August 2013. Association for Computational Linguistics.
• On the information conveyed by discourse markers. 
  Fatemeh Torabi Asr and Vera Demberg.
  In Proceedings of the ACL Workshop on Cognitive Modeling and Computational Linguistics (CMCL), pp. 84–93, Sofia, Bulgaria, 2013. Association for Computational Linguistics.
• Language and cognitive load in a dual task environment.
  Nikolaos Engonopoulos, Asad Sayeed, and Vera Demberg.
  In M. Knauff, M. Pauen, N. Sebanz, and I. Wachsmuth, editors, Proceedings of the 35th Annual Meeting of the Cognitive Science Society (CogSci-13), pp. 2249–2254, 2013.
• The index of cognitive activity as a measure of linguistic processing.
  Vera Demberg, Evangelia Kiagia, and Asad Sayeed.
  In M. Knauff, M. Pauen, N. Sebanz, and I. Wachsmuth, editors, Proceedings of the 35th Annual Meeting of the Cognitive Science Society (CogSci-13), pp. 2148–2153, 2013.
• Pupillometry: the index of cognitive activity in a dual-task study.
  Vera Demberg.
  In M. Knauff, M. Pauen, N. Sebanz, and I. Wachsmuth, editors, Proceedings of the 35th Annual Meeting of the Cognitive Science Society (CogSci-13), pp. 2154–2159, 2013.
• Integration costs on auxiliaries? – a self-paced reading study using webexp.
  Vera Demberg.
  In M. Knauff, M. Pauen, N. Sebanz, and I. Wachsmuth, editors, Proceedings of the 35th Annual Meeting of the Cognitive Science Society (CogSci-13), pp. 2160–2165, 2013.
• Identifying predictive collocations.
  Silas Weinbach and Vera Demberg.
  In M. Knauff, M. Pauen, N. Sebanz, and I. Wachsmuth, editors, Proceedings of the 35th Annual Conference of the Cognitive Science Society (CogSci-13), pp. 1581–1586, 2013.
• The Time-course of Processing Discourse Connectives.
  Judith Köhne and Vera Demberg.
  In M. Knauff, M. Pauen, N. Sebanz, and I. Wachsmuth, editors, Proceedings of the 35th Annual Meeting of the Cognitive Science Society (CogSci-13), pp. 2760–2765, 2013.

2 0 1 2

• Measuring the strength of linguistic cues for discourse relations.
  Fatemeh Torabi Asr and Vera Demberg.
  In Proceedings of the COLING Workshop on Advances in Discourse Analysis and its Computational Aspects (ADACA), pp. 33–42, Mumbai, India, 2012.
• Implicitness of discourse relations.
  Fatemeh Torabi Asr and Vera Demberg.
  In Proceedings of the 24th International Conference on Computational Linguistics (COLING), pp. 2669–2684, 2012.
• Incremental neo-davidsonian semantic construction for tag.
  Asad Sayeed and Vera Demberg.
  In 11th Work- shop on Tree-Adjoining Grammars and Related Formalisms (TAG+ 11), pp. 64–72, Paris, France, 2012.
• Incremental derivations in ccg.
  Vera Demberg.
  In Proceedings of the 11th International Workshop on Tree Adjoining Grammars and Related Formalisms (TAG+ 11), pp. 198–206, 2012.
• Syntactic surprisal affects spoken word duration in conversational contexts.
  Vera Demberg, Asad B Sayeed, Philip J Gorinski, and Nikolaos Engonopoulos.
  In Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, pp. 356–367. Association for Computational Linguistics, 2012.
• German and english treebanks and lexica for tree-adjoining grammars.
  Miriam Kaeshammer and Vera Demberg.
  In Proceedings of the 8th International Conference on Language Resources and Evaluation, pp. 1880–1887, 2012.

2 0 1 1

• Linguistic cognitive load: implications for automotive uis.
  Vera Demberg and Asad Sayeed.
  In Adjunct Proceedings of the 3rd International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI 2011), 2011.
• A strategy for information presentation in spoken dialog systems.
  Vera Demberg, Andi Winterboer, and Johanna D. Moore.
  Computational Linguistics, 37(3), pp. 489–539, 2011.

2 0 1 0

• A Broad-Coverage Model of Prediction in Human Sentence Processing. 
  Vera Demberg-Winterfors.
  PhD thesis, School of Informatics, The University of Edinburgh, 2010. Published in CPHC/BCS Distinguished Dissertations.
• Syntactic and semantic factors in processing difficulty: An integrated measure.
  Jeff Mitchell, Mirella Lapata, Vera Demberg, and Frank Keller.
  In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, pp. 196–206, Uppsala, Sweden, July 2010.

2 0 0 9

• A computational model of prediction in human parsing: Unifying locality and surprisal effects. 
  Vera Demberg and Frank Keller.
  In N. A. Taatgent and H. van Rijn, editors, Proceedings of the 31st meeting of the Cognitive Science Society, pp.1888–1893, Amsterdam, 2009.
• Correcting the incorrect: Local coherence effects modeled with prior belief update.
  Klinton Bicknell, Roger Levy, and Vera Demberg.
  In Proceedings of the 35th annual meeting of the Berkeley linguistics society, pp. 13–24, 2009.

2 0 0 8

• A psycholinguistically motivated version of TAG.
  Vera Demberg and Frank Keller.
  In Proceedings of the 9th International Workshop on Tree Adjoining Grammars and Related Formalisms (TAG+9), Tübingen, Germany, July 2008.
• Data from eye-tracking corpora as evidence for theories of syntactic processing complexity.
  Vera Demberg and Frank Keller. Cognition, 109, pp. 193–210, 2008.
• Syntactic complexity induces explicit grounding in the maptask corpus.
  Vera Demberg, Martin Tietze, and Johanna D. Moore.
  In Proceedings of Interspeech, Brisbane, Australia, 2008.

2 0 0 7

• Eye-tracking evidence for integration cost effects in corpus data.
  Vera Demberg and Frank Keller.
  In Proceedings of the 29th Annual Conference of the Cognitive Science Society, pp. 947–952, Nashville, 2007. Cognitive Science Society.
• Phonological constraints and morphological preprocessing for grapheme-to-phoneme conversion.
  Vera Demberg, Helmut Schmid, and Gregor Möhler.
  In Annual Meeting-Association For Computational Linguis- tics, volume 45, pages 97–103, 2007.
• A language-independent unsupervised model for morphological segmentation.
  Vera Demberg.
  In Annual Meeting-Association For Computational Linguistics, 45, pp. 920–927, 2007.

2 0 0 6

• Information presentation in spoken dialogue systems.
  Vera Demberg and Johanna D. Moore.
  In Proceedings of the 11th Conference of the European Chapter of the Association for Computational Linguistics, pp. 65–72, 2006.

2 0 0 3

• Tiger Annotationsschema. 
  Stefanie Albert, Jan Anderssen, Regine Bader, Stephanie Becker, Tobias Bracht, Sabine Brants, Thorsten Brants, Vera Demberg, Stefanie Dipper, Peter Eisenberg, et al.
  Universität des Saarlandes and Universität Stuttgart and Universität Potsdam, 2003.