2 citations · 2 across the 4 of their papers we have counts for
6 papers
Anchored Policy Optimization: Mitigating Exploration Collapse Via Support-Constrained Rectification
Tianyi Wang, Long Li, Hongcan Guo +5
Reinforcement Learning with Verifiable Rewards (RLVR) is increasingly viewed as a tree pruning mechanism. However, we identify a systemic pathology termed Recursive Space Contracti…
IIB-LPO: Latent Policy Optimization via Iterative Information Bottleneck
Huilin Deng, Hongchen Luo, Yue Zhu +8
Recent advances in Reinforcement Learning with Verifiable Rewards (RLVR) for Large Language Model (LLM) reasoning have been hindered by a persistent challenge: exploration collapse…
PaperAudit-Bench: Benchmarking Error Detection in Research Papers for Critical Automated Peer Review
Songjun Tu, Yiwen Ma, Jiahao Lin +6
Large language models can generate fluent peer reviews, yet their assessments often lack sufficient critical rigor when substantive issues are subtle and distributed across a paper…
Count Counts: Motivating Exploration in LLM Reasoning with Count-based Intrinsic Rewards
Xuan Zhang, Ruixiao Li, Zhijian Zhou +7
Reinforcement Learning (RL) has become a compelling way to strengthen the multi step reasoning ability of Large Language Models (LLMs). However, prevalent RL paradigms still lean o…
MMA-ASIA: A Multilingual and Multimodal Alignment Framework for Culturally-Grounded Evaluation
Weihua Zheng, Zhengyuan Liu, Tanmoy Chakraborty +32
Large language models (LLMs) are now used worldwide, yet their multimodal understanding and reasoning often degrade outside Western, high-resource settings. We propose MMA-ASIA, a…
To Code or not to Code? Adaptive Tool Integration for Math Language Models via Expectation-Maximization
Haozhe Wang, Long Li, Chao Qu +4
Recent advances in mathematical problem-solving with language models (LMs) integrate chain-of-thought (CoT) reasoning and code execution to harness their complementary strengths. H…