This article explains the key points of RbtAct: Rebuttal as Supervision for Actionable Review Feedback Generation. 2026-03-10 (arXiv) Wu, Sihong, Ma, Yiling, Zhao, Yilun, Hu, Tiansheng, Jiang, Owen, Patwardhan, Manasi, Cohan, Arman. Yale University, New York University, TCS Research Paper Github Read this article in Korean Summary RBTACT targets perspective-conditioned...

이번 글에서는 RbtAct: Rebuttal as Supervision for Actionable Review Feedback Generation 논문의 핵심 포인트만 간단히 정리한다. 2026년 3월 10일(Arxiv) Wu, Sihong, Ma, Yiling, Zhao, Yilun, Hu, Tiansheng, Jiang, Owen, Patwardhan, Manasi, Cohan, Arman. Yale University, New York University, TCS Research 논문 링크 Github 영문판 보기 요약 RBTACT는 관점 조건부 세그먼트...

This article explains the key points of Code-Space Response Oracles: Generating Interpretable Multi-Agent Policies with Large Language Models. 2026-03-10 (arXiv) Hennes, Daniel, Li, Zun, Schultz, John, Lanctot, Marc. Google DeepMind Paper Read this article in Korean Summary Code-Space Response Oracles (CSRO) replaces the reinforcement learning best-response oracle in Policy-Space Response...

이번 글에서는 Code-Space Response Oracles: Generating Interpretable Multi-Agent Policies with Large Language Models 논문의 핵심 포인트만 간단히 정리한다. 2026년 3월 10일(Arxiv) Hennes, Daniel, Li, Zun, Schultz, John, Lanctot, Marc. Google DeepMind 논문 링크 영문판 보기 요약 Code-Space Response Oracles (CSRO)는 Policy-Space Response Oracles (PSRO)의 강화학습 최적 응답 오라클을 실행 가능한...

This article explains the key points of KARL: Knowledge Agents via Reinforcement Learning. 2026-03-05 (arXiv) Chang, Jonathan D., Drozdov, Andrew, Toshniwal, Shubham, Oertell, Owen, Trott, Alexander, Portes, Jacob, Gupta, Abhay, Koppol, Pallavi, Baheti, Ashutosh, Kulinski, Sean, et al. Databricks AI Research Paper Read this article in Korean Summary KARL: Knowledge...