Introduces RevCI benchmark and IMPACT multi-agent framework for evidence-level contradiction detection and graded intensity scoring in peer reviews, distilled into efficient TIDE model.
The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval , pages =
3 Pith papers cite this work. Polarity classification is still indexing.
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Numerical scores predict ICLR acceptance at 91% accuracy while review text reaches only 81%, because politeness makes rejected papers' reviews contain more positive than negative words.
ATLAS is a multi-LLM agent framework that replaces fixed reference models with an inspection-agent-driven, proxy-KL-gated reference update inside EvoDPO and reports gains on non-stationary bandits, PINNs, and combinatorial tasks.
citing papers explorer
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When Reviews Disagree: Fine-Grained Contradiction Analysis in Scientific Peer Reviews
Introduces RevCI benchmark and IMPACT multi-agent framework for evidence-level contradiction detection and graded intensity scoring in peer reviews, distilled into efficient TIDE model.
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Decoupling Scores and Text: The Politeness Principle in Peer Review
Numerical scores predict ICLR acceptance at 91% accuracy while review text reaches only 81%, because politeness makes rejected papers' reviews contain more positive than negative words.
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ATLAS: A Multi-LLM Training Framework for EvoDPO with Adaptive Reference Evolution
ATLAS is a multi-LLM agent framework that replaces fixed reference models with an inspection-agent-driven, proxy-KL-gated reference update inside EvoDPO and reports gains on non-stationary bandits, PINNs, and combinatorial tasks.