Publications

• 2026
  When More Words Say Less: Decoupling Length and Specificity in Image Description Evaluation

  Rhea Kapur, Robert Hawkins, and Elisa Kreiss

  arXiv preprint arXiv:2601.04609
• 2026
  TABQAWORLD: Optimizing Multimodal Reasoning for Multi-Turn Table Question Answering

  Tung Sum Thomas Kwok, Xinyu Wang, Xiaofeng Lin, Peng Lu, Chunhe Wang, Changlun Li, Hanwei Wu, Nan Tang, Elisa Kreiss, and Guang Cheng

  arXiv preprint arXiv:2604.03393
• 2025
  Measuring Bias or Measuring the Task: Understanding the Brittle Nature of LLM Gender Biases

  Bufan Gao and Elisa Kreiss

  Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
• 2025
  MOSAIC: Modeling Social AI for Content Dissemination and Regulation in Multi-Agent Simulations

  Genglin Liu, Vivian T. Le, Salman Rahman, Elisa Kreiss, Marzyeh Ghassemi, and Saadia Gabriel

  Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
• 2025
  Meaningless Tokens, Meaningful Gains: How Activation Shifts Enhance LLM Reasoning

  Zeru Shi, Yingjia Wan, Zhenting Wang, Qifan Wang, Fan Yang, Elisa Kreiss, and Ruixiang Tang

  arXiv preprint arXiv:2510.01032
• 2024
  Reference-Based Metrics Are Biased Against Blind and Low-Vision Users' Image Description Preferences

  Rhea Kapur and Elisa Kreiss

  EMNLP: Third Workshop on NLP for Positive Impact

  Best Paper Award 🏆
• 2024
  CommVQA: Situating Visual Question Answering in Communicative Contexts

  Nandita Naik, Christopher Potts, and Elisa Kreiss

  Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
• 2024
  Evaluating human and machine understanding of data visualizations

  Arnav Verma, Kushin Mukherjee, Christopher Potts, Elisa Kreiss, and Judith Fan

  Proceedings of the Annual Meeting of the Cognitive Science Society
• 2024
  When Interpretability Enhances Accessibility: Training CLIP to Prefer Descriptions Over Captions

  Amir Zur, Elisa Kreiss, Karel D'Oosterlinck, Christopher Potts, and Atticus Geiger

  Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
• 2024
  ContextRef: Evaluating Referenceless Metrics For Image Description Generation

  Elisa Kreiss*, Eric Zelikman*, Christopher Potts, and Nick Haber

  The Twelfth International Conference on Learning Representations (ICLR)
• 2023
  A semantics for causing, enabling, and preventing verbs using structural causal models

  Angela Cao*, Atticus Geiger*, Elisa Kreiss*, Thomas Icard, and Tobias Gerstenberg

  Proceedings of the Annual Meeting of the Cognitive Science Society
• 2022
  Color Overmodification Emerges from Data-Driven Learning and Pragmatic Reasoning

  Fei Fang, Kunal Sinha, Noah D. Goodman, Christopher Potts, and Elisa Kreiss

  Proceedings of the Annual Meeting of the Cognitive Science Society
• 2022
  Inducing causal structure for interpretable neural networks

  Atticus Geiger, Zhengxuan Wu, Hanson Lu, Josh Rozner, Elisa Kreiss, Thomas Icard, Noah Goodman, and Christopher Potts

  International Conference on Machine Learning
• 2022
  Concadia: Towards Image-Based Text Generation with a Purpose

  Elisa Kreiss, Fei Fang, Noah Goodman, and Christopher Potts

  Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
• 2022
  Context Matters for Image Descriptions for Accessibility: Challenges for Referenceless Evaluation Metrics

  Elisa Kreiss, Cynthia Bennett, Shayan Hooshmand, Eric Zelikman, Meredith Ringel Morris, and Christopher Potts

  Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
• 2022
  Causal Distillation for Language Models

  Zhengxuan Wu, Atticus Geiger, Joshua Rozner, Elisa Kreiss, Hanson Lu, Thomas Icard, Christopher Potts, and Noah Goodman

  Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
• 2021
  ReaSCAN: Compositional Reasoning in Language Grounding

  Zhengxuan Wu*, Elisa Kreiss*, Desmond Ong, and Christopher Potts

  Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 1)
• 2020
  When redundancy is useful: A Bayesian approach to "overinformative" referring expressions.

  Judith Degen, Robert D Hawkins, Caroline Graf, Elisa Kreiss, and Noah D Goodman

  Psychological Review
• 2020
  Modeling Subjective Assessments of Guilt in Newspaper Crime Narratives

  Elisa Kreiss*, Zijian Wang*, and Christopher Potts

  Proceedings of the 24th Conference on Computational Natural Language Learning
• 2020
  Production expectations modulate contrastive inference.

  Elisa Kreiss and Judith Degen

  Proceedings of the Annual Meeting of the Cognitive Science Society
• 2019
  Uncertain evidence statements and guilt perception in iterative reproductions of crime stories.

  Elisa Kreiss, Michael Franke, and Judith Degen

  Proceedings of the Annual Meeting of the Cognitive Science Society