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Decision-Making with Deliberation: Meta-reviewing as a Document-grounded Dialogue

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Purkayastha, Sukannya, Dycke, Nils, Lauscher, Anne, Gurevych, Iryna·2026·Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
DOI 10.18653/v1/2026.eacl-long.158
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Sukannya Purkayastha, Nils Dycke, Anne Lauscher, Iryna Gurevych. Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers). 2026.

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  • Purkayastha et al. (2026) reframes meta-reviewing as a document-grounded dialogue problem, emphasizing deliberation and decision support beyond summarization alone.

    “Purkayastha et al. (2026) also reframes meta-reviewing as a document-grounded dialogue problem, emphasizing deliberation and decision support beyond summarization alone.”

    From Can AI Be a Good Peer Reviewer? A Survey of Peer Review Process, Evaluation, and the Future (2026) · cites this paper as Purkayastha et al., 2026

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  • Mistral 7B

    Jiang, A. Q., Sablayrolles, A., Mensch, A., Bamford, C., Chaplot, D. S., Casas, D. D. L., Bressand, F., Lengyel, G., Lample, G., Saulnier, L., et al. (2023) · arXiv · doi:10.48550/arxiv.2310.06825 · Cited by 340

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Research works printed but not linked: 72

  1. Vaibhav Adlakha, Parishad BehnamGhader, Xing Han Lu, Nicholas Meade, and Siva Reddy. 2024. Eval- uating correctness and faithfulness of instruction- following models for question answering. Trans- actions of the Association for Computational Linguis- tics, 12:681-699. · DOI · Paper page
  2. I. Aldasoro, L. Gambacorta, A. Korinek, V. Shreeti, and M. Stein. 2025. Intelligent financial system: How ai is transforming finance. Journal of Financial Sta- bility, 81:101472. https://doi.org/10.1016/j. jfs.2025.101472. · DOI
  3. Yuntao Bai, Andy Jones, Kamal Ndousse, Amanda Askell, Anna Chen, Nova DasSarma, Dawn Drain, Stanislav Fort, Deep Ganguli, Tom Henighan, Nicholas Joseph, Saurav Kadavath, Jackson Kernion, Tom Conerly, Sheer El-Showk, Nelson Elhage, Zac Hatfield-Dodds, Danny Hernandez, Tristan Hume, Scott Johnston, Shauna Kravec, Liane Lovitt, Neel Nanda, Catherine Olsson, Dario Amodei, Tom Brown, Jack Clark, Sam McCandlish, Chris Olah, Ben Mann, and Jared Kaplan. 2022. Training a help- ful and harmless assistant with reinforcement learn- ing from human feedback. ArXiv preprint arXiv: 2204.05862. · arXiv
  4. Wolf-Tilo Balke, Andreas Vlachos, Davide Ceolin, Mi- lad Alshomary, Nils Dycke, Sukannya Purkayastha, Iryna Gurevych, Anne Lauscher, and Tilman Beck. 2023. 5.4 scholarly argumentation as a community dialogue. Dagstuhl Reports, 12(10):202. https: //doi.org/10.4230/DagRep.12.10.175. · DOI
  5. Jianzhu Bao, Rui Wang, Yasheng Wang, Aixin Sun, Yitong Li, Fei Mi, and Ruifeng Xu. 2023. A synthetic data generation framework for grounded dialogues. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 10866-10882, Toronto, Canada. Association for Computational Linguistics. · DOI
  6. Ning Bian, Xianpei Han, Le Sun, Hongyu Lin, Yao- jie Lu, Ben He, Shanshan Jiang, and Bin Dong. 2024. ChatGPT is a knowledgeable but inexperi- enced solver: An investigation of commonsense prob- lem in large language models. In Proceedings of the 2024 Joint International Conference on Computa- tional Linguistics, Language Resources and Eval- uation (LREC-COLING 2024), pages 3098-3110, Torino, Italia. ELRA and ICCL.
  7. Jordan Boyd-Graber, Naoaki Okazaki, and Anna Rogers. 2023. ACL'23 Peer Review Policies. https: //2023.aclweb.org/blog/review-acl23/. Ac- cessed: 2025-12-02.
  8. Justin Chen, Swarnadeep Saha, and Mohit Bansal. 2024a. ReConcile: Round-Table Conference Im- proves Reasoning via Consensus among Diverse LLMs. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Vol- ume 1: Long Papers), pages 7066-7085, Bangkok, Thailand. Association for Computational Linguistics. · DOI · Paper page
  9. Maximillian Chen, Alexandros Papangelis, Chenyang Tao, Seokhwan Kim, Andy Rosenbaum, Yang Liu, Zhou Yu, and Dilek Hakkani-Tur. 2023. PLACES: Prompting language models for social conversation synthesis. In Findings of the Association for Com- putational Linguistics: EACL 2023, pages 844-868, Dubrovnik, Croatia. Association for Computational Linguistics.
  10. Pinzhen Chen, Zhicheng Guo, Barry Haddow, and Ken- neth Heafield. 2024b. Iterative Translation Refine- ment with Large Language Models. In Proceedings of the 25th Annual Conference of the European As- sociation for Machine Translation (Volume 1), pages 181-190, Sheffield, UK. European Association for Machine Translation (EAMT).
  11. Xieling Chen, Haoran Xie, and Xiaohui Tao. 2022. Vision, status, and research topics of natural lan- guage processing. Natural Language Processing Journal, 1:100001. https://doi.org/10.1016/j. nlp.2022.100001. · DOI
  12. Ton J. Cleophas and Aeilko H. Zwinderman. 2010. Paired Continuous Data (Paired- t, Wilcoxon) (10 Patients), pages 7-9. Springer Netherlands, Dordrecht. https: //doi.org/10.1007/978-90-481-9519-0_3. · DOI
  13. Nico Daheim, Nouha Dziri, Mrinmaya Sachan, Iryna Gurevych, and Edoardo Ponti. 2024. Elastic weight removal for faithful and abstractive dialogue gener- ation. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Tech- nologies (Volume 1: Long Papers), pages 7096-7112, Mexico City, Mexico. Association for Computational Linguistics. · DOI · Paper page
  14. Zhuyun Dai, Arun Tejasvi Chaganty, Vincent Y. Zhao, Aida Amini, Qazi Mamunur Rashid, Mike Green, and Kelvin Guu. 2022. Dialog inpainting: Turning docu- ments into dialogs. In International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Bal- timore, Maryland, USA, volume 162 of Proceedings of Machine Learning Research, pages 4558-4586.
  15. PMLR.
  16. Tjibbe Donker. 2023. The dangers of using large lan- guage models for peer review. The Lancet Infectious Diseases, 23(7):781. https://doi.org/10.1016/ S1473-3099(23)00290-6. · DOI
  17. Nils Dycke, Ilia Kuznetsov, and Iryna Gurevych. 2023. NLPeer: A unified resource for the computational study of peer review. In Proceedings of the 61st An- nual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 5049- 5073, Toronto, Canada. Association for Computa- tional Linguistics. · DOI · Paper page
  18. Nouha Dziri, Ehsan Kamalloo, Sivan Milton, Os- mar Zaiane, Mo Yu, Edoardo M. Ponti, and Siva Reddy. 2022. FaithDial: A Faithful Benchmark for Information-Seeking Dialogue. Transactions of the Association for Computational Linguistics, 10:1473- 1490. · DOI
  19. Youmna Farag, Charlotte Brand, Jacopo Amidei, Paul Piwek, Tom Stafford, Svetlana Stoyanchev, and An- dreas Vlachos. 2022. Opening up minds with argu- mentative dialogues. In Findings of the Association for Computational Linguistics: EMNLP 2022, pages 4569-4582, Abu Dhabi, United Arab Emirates. As- sociation for Computational Linguistics.
  20. Xue-Yong Fu, Md Tahmid Rahman Laskar, Elena Khasanova, Cheng Chen, and Shashi Tn. 2024. Tiny titans: Can smaller large language models punch above their weight in the real world for meeting sum- marization? In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Tech- nologies (Volume 6: Industry Track), pages 387-394, Mexico City, Mexico. Association for Computational Linguistics. · DOI
  21. Iftah Gamzu, Hila Gonen, Gilad Kutiel, Ran Levy, and Eugene Agichtein. 2021. Identifying helpful sen- tences in product reviews. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Hu- man Language Technologies, pages 678-691, Online. Association for Computational Linguistics. · DOI
  22. Kate Goddard, Abdul Roudsari, and Jeremy C. Wyatt. 2014. Automation bias: Empirical results assessing influencing factors. International Journal of Medical Informatics, 83(5):368-375. https://doi.org/10. 1016/j.ijmedinf.2014.01.001. · DOI · Paper page
  23. Roberta Michnick Golinkoff, Erika Hoff, Meredith L Rowe, Catherine S Tamis-LeMonda, and Kathy Hirsh-Pasek. 2019. Language matters: Denying the existence of the 30-million-word gap has serious consequences. Child development, 90(3):985-992. https://doi.org/10.1111/cdev.13128. · DOI
  24. Pengcheng He, Xiaodong Liu, Jianfeng Gao, and Weizhu Chen. 2021. DEBERTA: Decoding- Enhanced BERT with Disentangled Attention. In 9th International Conference on Learning Represen- tations, ICLR 2021, Virtual, May 03-07, 2021. Open- review.net.
  25. Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi. 2020. The curious case of neural text degeneration. In Proceedings of the 8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020. OpenRe- view.net.
  26. Or Honovich, Leshem Choshen, Roee Aharoni, Ella Neeman, Idan Szpektor, and Omri Abend. 2021. q 2 : Evaluating factual consistency in knowledge- grounded dialogues via question generation and ques- tion answering. In Proceedings of the 2021 Confer- ence on Empirical Methods in Natural Language Pro- cessing, pages 7856-7870, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics. · DOI · Paper page
  27. Eftekhar Hossain, Sanjeev Kumar Sinha, Naman Bansal, R. Alexander Knipper, Souvika Sarkar, John Sal- vador, Yash Mahajan, Sri Ram Pavan Kumar Gut- tikonda, Mousumi Akter, Md. Mahadi Hassan, Matthew Freestone, Matthew C. Williams Jr., Dongji Feng, and Santu Karmaker. 2025. LLMs as meta- reviewers' assistants: A case study. In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Lin- guistics: Human Language Technologies (Volume 1: Long Papers), pages 7763-7803, Albuquerque, New Mexico. Association for Computational Linguistics. · DOI · Paper page
  28. Cheng-Yu Hsieh, Chun-Liang Li, Chih-kuan Yeh, Hootan Nakhost, Yasuhisa Fujii, Alex Ratner, Ranjay Krishna, Chen-Yu Lee, and Tomas Pfister. 2023. Dis- tilling step-by-step! outperforming larger language models with less training data and smaller model sizes. In Findings of the Association for Compu- tational Linguistics: ACL 2023, pages 8003-8017, Toronto, Canada. Association for Computational Lin- guistics. · DOI · Paper page
  29. Zhengyu Hu, Linxin Song, Jieyu Zhang, Zheyuan Xiao, Tianfu Wang, Zhengyu Chen, Nicholas Jing Yuan, Jianxun Lian, Kaize Ding, and Hui Xiong. 2025. Ex- plaining length bias in LLM-based preference evalu- ations. In Findings of the Association for Computa- tional Linguistics: EMNLP 2025, pages 6763-6794, Suzhou, China. Association for Computational Lin- guistics. · DOI · Paper page
  30. Jie Huang, Xinyun Chen, Swaroop Mishra, Huaixiu Steven Zheng, Adams Wei Yu, Xiny- ing Song, and Denny Zhou. 2024. Large language models cannot self-correct reasoning yet. In 12th International Conference on Learning Representa- tions, ICLR 2024, Vienna, Austria, May 07-11, 2024. Openreview.net.
  31. Albert Q. Jiang, Alexandre Sablayrolles, Antoine Roux, Arthur Mensch, Blanche Savary, Chris Bamford, De- vendra Singh Chaplot, Diego de las Casas, et al. 2024. Mixtral of Experts. ArXiv preprint arXiv: 2401.04088. · arXiv
  32. Aishwarya Kamath, Johan Ferret, Shreya Pathak, Nino Vieillard, Ramona Merhej, Sarah Perrin, Tatiana Matejovicova, et al. 2025. Gemma 3 technical re- port. Arxiv preprint arXiv: 2503.19786. · arXiv
  33. Yuhe Ke, Rui Yang, Sui An Lie, Taylor Xin Yi Lim, Yilin Ning, Irene Li, Hairil Rizal Abdullah, Daniel Shu Wei Ting, and Nan Liu. 2024. Mitigating cog- nitive biases in clinical decision-making through multi-agent conversations using large language mod- els: simulation study. Journal of Medical Internet Research, 26:e59439. https://doi.org/10.2196/ 59439. · DOI · Paper page
  34. Neha Nayak Kennard, Tim O'Gorman, Rajarshi Das, Akshay Sharma, Chhandak Bagchi, Matthew Clin- ton, Pranay Kumar Yelugam, Hamed Zamani, and Andrew McCallum. 2022. DISAPERE: A dataset for discourse structure in peer review discussions. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computa- tional Linguistics: Human Language Technologies, pages 1234-1249, Seattle, United States. Association for Computational Linguistics. · DOI · Paper page
  35. Mario Krenn, Lorenzo Buffoni, Bruno Coutinho, Sagi Eppel, Jacob Gates Foster, Andrew Gritsevskiy, Har- lin Lee, Yichao Lu, João P. Moutinho, Nima Sanjabi, Rishi Sonthalia, Ngoc Mai Tran, Francisco Valente, Yangxinyu Xie, Rose Yu, and Michael Kopp. 2023. Forecasting the future of artificial intelligence with machine learning-based link prediction in an expo- nentially growing knowledge network. Nature Ma- chine Intelligence, 5(11). http://dx.doi.org/10. 1038/s42256-023-00735-0. · DOI
  36. Ilia Kuznetsov, Osama Mohammed Afzal, Koen Der- cksen, Nils Dycke, Alexander Goldberg, Tom Hope, Dirk Hovy, et al. 2024. What can natural language processing do for peer review? ArXiv preprint arXiv: 2405.06563. · arXiv
  37. Vivian Lai, Chacha Chen, Alison Smith-Renner, Q. Vera Liao, and Chenhao Tan. 2023. Towards a science of human-ai decision making: An overview of design space in empirical human-subject studies. In Pro- ceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, FAccT '23, page 1369-1385, New York, NY, USA. Association for Computing Machinery. · DOI · Paper page
  38. Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut. 2020. ALBERT: A lite BERT for Self-supervised Learning of Language Representations. In Proceed- ings of the 8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020. OpenReview.net.
  39. Rosemary Lever and Monique Sénéchal. 2011. Dis- cussing stories: On how a dialogic reading inter- vention improves kindergartners' oral narrative con- struction. Journal of experimental child psychology, 108(1):1-24. https://doi.org/10.1016/j.jecp. 2010.07.002. · DOI
  40. Junyi Jessy Li and Ani Nenkova. 2015. Fast and accu- rate prediction of sentence specificity. In Proceed- ings of the Twenty-Ninth AAAI Conference on Artifi- cial Intelligence, January 25-30, 2015, Austin, Texas, USA, pages 2281-2287. AAAI Press.
  41. Miao Li, Eduard Hovy, and Jey Lau. 2023a. Summariz- ing multiple documents with conversational structure for meta-review generation. In Findings of the As- sociation for Computational Linguistics: EMNLP 2023, pages 7089-7112, Singapore. Association for Computational Linguistics. · DOI
  42. Siheng Li, Cheng Yang, Yichun Yin, Xinyu Zhu, Ze- sen Cheng, Lifeng Shang, Xin Jiang, Qun Liu, and Yujiu Yang. 2023b. AutoConv: Automatically gen- erating information-seeking conversations with large language models. In Proceedings of the 61st Annual Meeting of the Association for Computational Lin- guistics (Volume 2: Short Papers), pages 1751-1762, Toronto, Canada. Association for Computational Lin- guistics. · DOI
  43. Jessy Lin, Nicholas Tomlin, Jacob Andreas, and Jason Eisner. 2024. Decision-oriented dialogue for human- AI collaboration. Transactions of the Association for Computational Linguistics, 12:892-911. · DOI
  44. Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Man- dar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019. RoBERTa: A Robustly Optimized BERT Pretraining Approach. Arxiv preprint arXiv: 1907.11692. · arXiv
  45. Shayne Longpre, Le Hou, Tu Vu, Albert Webson, Hyung Won Chung, Yi Tay, Denny Zhou, Quoc V Le, Barret Zoph, Jason Wei, and Adam Roberts. 2023. The Flan Collection: Designing Data and Methods for Effective Instruction Tuning. In Proceedings of the 40th International Conference on Machine Learn- ing, ICML 2023, Honolulu Hawaii USA, July 23 -29, 2023. PMLR.
  46. Edisa Lozić and Benjamin Štular. 2023. Fluent but not factual: A comparative Analysis of Chatgpt and other AI chatbots' Proficiency and Originality in Scien- tific Writing for Humanities. Future Internet, 15(10). https://doi.org/10.3390/fi15100336. · DOI
  47. Jakub Macina, Nico Daheim, Sankalan Chowdhury, Tan- may Sinha, Manu Kapur, Iryna Gurevych, and Mrin- maya Sachan. 2023. MathDial: A dialogue tutoring dataset with rich pedagogical properties grounded in math reasoning problems. In Findings of the As- sociation for Computational Linguistics: EMNLP 2023, pages 5602-5621, Singapore. Association for Computational Linguistics. · DOI
  48. Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, Shashank Gupta, Bodhisattwa Prasad Majumder, Katherine Hermann, Sean Welleck, Amir Yazdan- bakhsh, and Peter Clark. 2023. Self-refine: Iterative Refinement with Self-Feedback. In Proceedings of the Thirty-seventh Conference on Neural Information Processing Systems, NeurIPS 2023, New Orleans, USA. Openreview.net.
  49. Anders Giovanni Møller, Jacob Aarup Dalsgaard, Ari- anna Pera, and Luca Maria Aiello. 2023. Is a Prompt and a few samples all you need? using GPT-4 for data augmentation in low-resource classification tasks. Arxiv preprint arXiv: 2304.13861. · arXiv
  50. Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Gray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul Christiano, Jan Leike, and Ryan Lowe. 2022. Training language models to follow instructions with human feedback. In Proceedings of the Thirty-sixth Conference on Neural Information Processing Sys- tems, NeurIPS 2022, New Orleans, USA (Hybrid), Nov 28-Dec 09, 2022. Openreview.net.
  51. Matt Post. 2018. A call for clarity in reporting BLEU scores. In Proceedings of the Third Conference on Machine Translation: Research Papers, pages 186- 191, Brussels, Belgium. Association for Computa- tional Linguistics. · DOI · Paper page
  52. Priyanshu Priya, Saurav Dudhate, Desai Vishesh Yasheshbhai, and Asif Ekbal. 2025. We argue to agree: Towards personality-driven argumentation- based negotiation dialogue systems for tourism. In Findings of the Association for Computational Lin- guistics: EMNLP 2025, pages 25504-25536, Suzhou, China. Association for Computational Linguistics. · DOI
  53. Sukannya Purkayastha, Anne Lauscher, and Iryna Gurevych. 2023. Exploring jiu-jitsu argumentation for writing peer review rebuttals. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 14479-14495, Singapore. Association for Computational Linguis- tics. · DOI
  54. Colin Raffel, Noam Shazeer, Adam Roberts, Kather- ine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020. Exploring the limits of transfer learning with a unified text- to-text transformer. Journal of Machine Learning Research, 21:140:1-140:67. https://dl.acm.org/ doi/10.5555/3455716.3455856. · DOI
  55. Hannah Rashkin, David Reitter, Gaurav Singh Tomar, and Dipanjan Das. 2021. Increasing faithfulness in knowledge-grounded dialogue with controllable features. In Proceedings of the 59th Annual Meet- ing of the Association for Computational Linguistics and the 11th International Joint Conference on Natu- ral Language Processing (Volume 1: Long Papers), pages 704-718, Online. Association for Computa- tional Linguistics. · DOI · Paper page
  56. Max Schemmer, Niklas Kühl, Carina Benz, and Ger- hard Satzger. 2022. On the influence of explainable ai on automation bias. In Proceedings of the 30th Eu- ropean Conference on Information Systems (ECIS), Timis , oara, RO, June 18-24, 2022. aisel.aisnet.org.
  57. Laurie A Schintler, Connie L McNeely, and James Witte. 2023. A Critical Examination of the ethics of AI-Mediated Peer Review. Arxiv preprint arXiv: 2309.12356. · arXiv
  58. Chenhui Shen, Liying Cheng, Ran Zhou, Lidong Bing, Yang You, and Luo Si. 2022. MReD: A meta-review dataset for structure-controllable text generation. In Findings of the Association for Computational Lin- guistics: ACL 2022, pages 2521-2535, Dublin, Ire- land. Association for Computational Linguistics. · DOI · Paper page
  59. Daniel Smolyak, Margrét V Bjarnadóttir, Kenyon Crow- ley, and Ritu Agarwal. 2024. Large language models and synthetic health data: progress and prospects. JAMIA Open, 7(4):ooae114. https://doi.org/10. 1093/jamiaopen/ooae114. · DOI
  60. Katherine Stasaski, Kimberly Kao, and Marti A. Hearst. 2020. CIMA: A large open access dialogue dataset for tutoring. In Proceedings of the Fifteenth Work- shop on Innovative Use of NLP for Building Educa- tional Applications, pages 52-64, Seattle, WA, USA → Online. Association for Computational Linguis- tics. · DOI
  61. Hugo Touvron, Louis Martin, Kevin Stone, Peter Al- bert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, Dan Bikel, et al. 2023. Llama 2: Open foun- dation and fine-tuned chat models. ArXiv preprint arXiv: 2307.09288. · arXiv
  62. Xuewei Wang, Weiyan Shi, Richard Kim, Yoojung Oh, Sijia Yang, Jingwen Zhang, and Zhou Yu. 2019. Per- suasion for good: Towards a personalized persuasive dialogue system for social good. In Proceedings of the 57th Annual Meeting of the Association for Com- putational Linguistics, pages 5635-5649, Florence, Italy. Association for Computational Linguistics. · DOI · Paper page
  63. Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V Le, Ed H. Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou. 2023. Self-consistency improves chain of thought reasoning in language models. In Proceedings of the 11th International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 01-05, 2023. Openreview.net.
  64. Ziqi Wang, Le Hou, Tianjian Lu, Yuexin Wu, Yunx- uan Li, Hongkun Yu, and Heng Ji. 2024. En- abling lanuguage models to implicitly learn self- improvement. In 12th International Conference on Learning Representations, ICLR 2024, Vienna, Aus- tria, May 07-11, 2024. OpenReview.Net.
  65. Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pier- ric Cistac, Tim Rault, Remi Louf, Morgan Funtow- icz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush. 2020. Trans- formers: State-of-the-art natural language processing. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 38-45, Online. Association for Computational Linguistics. · DOI · Paper page
  66. Po-Cheng Wu, An-Zi Yen, Hen-Hsen Huang, and Hsin- Hsi Chen. 2022a. Incorporating peer reviews and rebuttal counter-arguments for meta-review genera- tion. In Proceedings of the 31st ACM International Conference on Information & Knowledge Manage- ment, CIKM '22, page 2189-2198, New York, NY, USA. Association for Computing Machinery. · DOI
  67. Qingyang Wu, Song Feng, Derek Chen, Sachindra Joshi, Luis Lastras, and Zhou Yu. 2022b. DG2: Data aug- mentation through document grounded dialogue gen- eration. In Proceedings of the 23rd Annual Meeting of the Special Interest Group on Discourse and Dia- logue, pages 204-216, Edinburgh, UK. Association for Computational Linguistics.
  68. An Yang, Anfeng Li, Baosong Yang, Beichen Zhang, Binyuan Hui, Bo Zheng, Bowen Yu, Chang Gao, Chengen Huang, Chenxu Lv, Chujie Zheng, et al. 2025. Qwen3 technical report. Arxiv preprint arXiv: 2505.09388. · arXiv
  69. Qi Zeng, Mankeerat Sidhu, Ansel Blume, Hou Pong Chan, Lu Wang, and Heng Ji. 2025. Scientific opin- ion summarization: Paper meta-review generation dataset, methods, and evaluation. In Artificial Intel- ligence for Research and Democracy: First Interna- tional Workshop, AI4Research 2024, and 4th Interna- tional Workshop, DemocrAI 2024, Held in Conjunc- tion with IJCAI 2024, Jeju, South Korea, August 5, 2024, Proceedings, page 20-38, Berlin, Heidelberg. Springer-Verlag. · DOI · Paper page
  70. Justine Zhang, Ravi Kumar, Sujith Ravi, and Cris- tian Danescu-Niculescu-Mizil. 2016. Conversational flow in Oxford-style debates. In Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Hu- man Language Technologies, pages 136-141, San Diego, California. Association for Computational Linguistics. · DOI
  71. Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, et al. 2022. OPT: Open Pre-trained Transformer Language Models. ArXiv preprint arXiv: 2205.01068. · arXiv
  72. Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, and Yoav Artzi. 2020. Bertscore: Evalu- ating text generation with BERT. In Proceedings of the 8th International Conference on Learning Repre- sentations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020. OpenReview.net.

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Metadata

Authors
Purkayastha, S., Dycke, N., Lauscher, A., & Gurevych, I.
Affiliations
  • Technische Universität Darmstadt (DE)
  • Universität Hamburg (DE)
ORCID
Venue
Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
Publisher
Association for Computational Linguistics
Published
2026
Pages
3424-3465
DOI
10.18653/v1/2026.eacl-long.158
OpenAlex
W7140124164
Cited by
2
References
1
Citations by year
2026: 2
FWCI
2.75
Type
conference paper
Language
en
Open access
Licence
cc-by
Locations
  • Conference of the European Chapter of the Association for Computational Linguistics (publishedVersion, cc-by)
  • TUbilio (Technical University of Darmstadt) (acceptedVersion)
  • arXiv (Cornell University) (submittedVersion, other-oa)
  • arXiv (Cornell University)
Funders
  • Australian Government
  • Deutsche Forschungsgemeinschaft (GRK 2222)
  • Bundesministerium für Bildung und Forschung
  • Leibniz-Gemeinschaft
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Sentiment Analysis and Opinion Mining
  • Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
  • Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
Keywords
deliberation, decision-making, peer review, human-computer dialogue

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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