Kaitlyn Zhou
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
13
Venues
4
Active years
2016–2026
Best venue rank
A*
Where they publish
Papers
13 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | ACL | ReasonIF: Large Reasoning Models Fail to Follow Instructions During Reasoning. | Yongchan Kwon, Shang Zhu, Federico Bianchi, Kaitlyn Zhou, James Zou |
| 2026 | ACL | Attention to Non-Adopters. | Kaitlyn Zhou, Kristina Gligoric, Myra Cheng, Michelle S. Lam, Vyoma Raman, Boluwatife Aminu, Caeley Woo, Michael Brockman, Hannah Cha, Dan Jurafsky |
| 2025 | ACL | ELI-Why: Evaluating the Pedagogical Utility of Language Model Explanations. | Brihi Joshi, Keyu He, Sahana Ramnath, Sadra Sabouri, Kaitlyn Zhou, Souti Chattopadhyay, Swabha Swayamdipta, Xiang Ren |
| 2025 | NAACL | Rethinking Word Similarity: Semantic Similarity through Classification Confusion. | Kaitlyn Zhou, Haishan Gao, Sarah Li Chen, Dan Edelstein, Dan Jurafsky, Chen Shani |
| 2025 | NAACL | REL-A.I.: An Interaction-Centered Approach To Measuring Human-LM Reliance. | Kaitlyn Zhou, Jena D. Hwang, Xiang Ren, Nouha Dziri, Dan Jurafsky, Maarten Sap |
| 2024 | ACL | Relying on the Unreliable: The Impact of Language Models' Reluctance to Express Uncertainty. | Kaitlyn Zhou, Jena D. Hwang, Xiang Ren, Maarten Sap |
| 2023 | EMNLP | Navigating the Grey Area: How Expressions of Uncertainty and Overconfidence Affect Language Models. | Kaitlyn Zhou, Dan Jurafsky, Tatsunori Hashimoto |
| 2022 | ACL | Problems with Cosine as a Measure of Embedding Similarity for High Frequency Words. | Kaitlyn Zhou, Kawin Ethayarajh, Dallas Card, Dan Jurafsky |
| 2022 | ACL | Richer Countries and Richer Representations. | Kaitlyn Zhou, Kawin Ethayarajh, Dan Jurafsky |
| 2022 | NAACL | Deconstructing NLG Evaluation: Evaluation Practices, Assumptions, and Their Implications. | Kaitlyn Zhou, Su Lin Blodgett, Adam Trischler, Hal Daum III, Kaheer Suleman, Alexandra Olteanu |
| 2021 | CHI | The Disagreement Deconvolution: Bringing Machine Learning Performance Metrics In Line With Reality. | Mitchell L. Gordon, Kaitlyn Zhou, Kayur Patel, Tatsunori Hashimoto, Michael S. Bernstein |
| 2017 | CHI | Centralized, Parallel, and Distributed Information Processing during Collective Sensemaking. | Peter M. Krafft, Kaitlyn Zhou, Isabelle Edwards, Kate Starbird, Emma S. Spiro |
| 2016 | CHI | Could This Be True?: I Think So! Expressed Uncertainty in Online Rumoring. | Kate Starbird, Emma S. Spiro, Isabelle Edwards, Kaitlyn Zhou, Jim Maddock, Sindhuja Narasimhan |