Gurevych, Iryna

Attribute or Abstain: Large Language Models as Long Document Assistants

Buchmann, J., Liu, X., & Gurevych, I. (2024) · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing

Topic ModelingInformation Retrieval and Search Behavior

Cited by 3

PeerQA: A Scientific Question Answering Dataset from Peer Reviews

Baumgärtner, T., Briscoe, T., & Gurevych, I. (2025) · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)

Expert finding and Q&A systemsTopic Modeling

Cited by 3

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

Purkayastha, S., Dycke, N., Lauscher, A., & Gurevych, I. (2026) · Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)

Sentiment Analysis and Opinion MiningTopic Modeling

Cited by 2

RIRAG: Regulatory Information Retrieval and Answer Generation

Gokhan, T., Wang, K., Gurevych, I., & Briscoe, T. (2024) · arXiv

Topic ModelingArtificial Intelligence in Law

Cited by 1

Automatic Reviewers Fail to Detect Faulty Reasoning in Research Papers: A New Counterfactual Evaluation Framework

Dycke, N., & Gurevych, I. (2025) · arXiv

Academic Writing and PublishingTopic Modeling

Cited by 1

Automatic Reviewers Fail to Detect Faulty Reasoning in Research Papers: A New Counterfactual Evaluation Framework

Dycke, N., & Gurevych, I. (2026) · Transactions of the Association for Computational Linguistics

Academic Writing and PublishingTopic Modeling

Cited by 1

STRICTA: Structured Reasoning in Critical Text Assessment for Peer Review and Beyond

Dycke, N., Zečević, M., Kuznetsov, I., Suess, B., Kersting, K., & Gurevych, I. (2025) · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Natural Language Processing TechniquesDiscourse Analysis in Language Studies

Cited by 1

The Good, the Bad and the Constructive: Automatically Measuring Peer Review’s Utility for Authors

Sadallah, A., Baumgärtner, T., Gurevych, I., & Briscoe, T. (2025) · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing

Academic Writing and PublishingPublishing and Scholarly Communication

Cited by 1

NLPeer: A Unified Resource for the Computational Study of Peer Review

Dycke, N., Kuznetsov, I., & Gurevych, I. (2022) · arXiv

Publishing and Scholarly CommunicationAcademic Writing and Publishing

Cited by 1

LazyReview A Dataset for Uncovering Lazy Thinking in NLP Peer Reviews

Purkayastha, S., Li, Z., Lauscher, A., Qu, L., & Gurevych, I. (2025) · arXiv

Academic Writing and PublishingTopic Modeling

Cited by 1

Elastic Weight Removal for Faithful and Abstractive Dialogue Generation

Daheim, N., Dziri, N., Sachan, M., Gurevych, I., & Ponti, E. M. (2023) · arXiv

Speech and dialogue systemsTopic Modeling

Cited by 0

Attribute or Abstain: Large Language Models as Long Document Assistants

Buchmann, J., Liu, X., & Gurevych, I. (2024) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 0

SciCoQA: Quality Assurance for Scientific Paper-Code Alignment

Baumgärtner, T., & Gurevych, I. (2026) · arXiv

Software Engineering ResearchScientific Computing and Data Management

Cited by 0

PeerQA: A Scientific Question Answering Dataset from Peer Reviews

Baumgärtner, T., Briscoe, T., & Gurevych, I. (2025) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 0