Does Math Reasoning Improve General LLM Capabilities? Understanding Transferability of LLM Reasoning
Maggie Huan, Yuetai Li, Tuney Zheng, Xiaoyu Xu, Seungone Kim, Minxin Du, Radha Poovendran, Graham Neubig, Xiang Yue
机构
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Carnegie Mellon University(卡内基梅隆大学)
;
University of Pennsylvania(宾夕法尼亚大学)
;
University of Washington(华盛顿大学)
;
M-A-P
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The Hong Kong Polytechnic University(香港理工大学)
专题命中
推理与问题求解
:LLM(title);large language model(abstract);language model(abstract);post-training(abstract)
MALT: Improving Reasoning with Multi-Agent LLM Training
Sumeet Ramesh Motwani, Chandler Smith, Rocktim Jyoti Das, Rafael Rafailov, Ivan Laptev, Philip H. S. Torr, Fabio Pizzati, Ronald Clark, Christian Schroeder de Witt
机构
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University of Oxford(牛津大学)
;
Cooperative AI Foundation(合作人工智能基金会)
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MBZUAI(穆扎夫卡尔人工智能研究所)
;
Stanford University(斯坦福大学)
专题命中
推理与问题求解
:LLM(title,abstract);large language model(abstract);language model(abstract);post-training(abstract)
Metacognitive Reuse: Turning Recurring LLM Reasoning Into Concise Behaviors
Aniket Didolkar, Nicolas Ballas, Sanjeev Arora, Anirudh Goyal
机构
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Meta
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Mila-Quebec AI Institute, University of Montreal(魁北克AI研究所,蒙特利尔大学)
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Princeton University(普林斯顿大学)
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Mila--Quebec AI Institute, Université de Montréal(魁北克AI研究所,蒙特利尔大学)
专题命中
推理与问题求解
:LLM(title,abstract);large language model(abstract);language model(abstract);SFT(abstract)
Improving LLM Reasoning for Vulnerability Detection via Group Relative Policy Optimization
Marco Simoni, Aleksandar Fontana, Giulio Rossolini, Andrea Saracino
机构
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Institute of Informatics and Telematics, National Research Council of Italy(意大利国家研究理事会信息与电信研究所)
;
Department of Excellence in Robotics and AI, TeCIP, Scuola Superiore Sant'Anna(卓越机器人与人工智能系,TeCIP,圣安娜高等学院)
专题命中
推理与问题求解
:LLM(title,abstract);large language model(abstract);language model(abstract);SFT(abstract)
机构
*
California Institute of Technology(加州理工学院)
;
UCLA(加州大学洛杉矶分校)
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National University of Singapore(新加坡国立大学)
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Hangzhou Dianzi University(杭州电子科技大学)
;
Fudan University(复旦大学)
专题命中
推理与问题求解
:LLM(title,abstract);large language model(abstract);language model(abstract);pretraining(abstract)