2 citations · 5 across the 20 of their papers we have counts for
4 papers · 2 filters
Verifiable Environments Are LEGO Bricks: Recursive Composition for Reasoning Generalization
Hao Xiang, Qiaoyu Tang, Le Yu +8
Reinforcement Learning (RL) with verifiable environments has emerged as a powerful approach for enhancing the reasoning capabilities of Large Language Models (LLMs). While prior re…
Your Teacher Can't Help You Here: Combating Supervision Fidelity Decay in On-Policy Distillation
Yanjiang Liu, Jie Lou, Xinyan Guan +7
On-policy distillation transfers reasoning capabilities by training a student model on its own generated trajectories using token-level feedback from a teacher. However, we identif…
All Languages Matter: Understanding and Mitigating Language Bias in Multilingual RAG
Dan Wang, Guozhao Mo, Yafei Shi +9
Multilingual Retrieval-Augmented Generation (mRAG) leverages cross-lingual evidence to ground Large Language Models (LLMs) in global knowledge. However, we show that current mRAG s…
Identifying and Transferring Reasoning-Critical Neurons: Improving LLM Inference Reliability via Activation Steering
Fangan Dong, Zuming Yan, Xuri Ge +7
Despite the strong reasoning capabilities of recent large language models (LLMs), achieving reliable performance on challenging tasks often requires post-training or computationall…