Papers by Vidushee Vats
Preference Optimization for Review Question Generation Improves Writing Quality (2026.findings-acl)
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| Challenge: | Peer reviewers are overloaded and face tight deadlines, leading some to rely on large language models (LLMs) to draft questions and comments. |
| Approach: | They use open-review review datasets to train a human preference model based on human reviewer questions . human evaluations show IntelliAsk generates more grounded, substantive and effortful questions than strong baselines . |
| Outcome: | The proposed model predicts reviewer-question quality better than API-based SFT baselines and provides scalable evaluation. |