4 papers · 1 filter
Towards Effective Experiential Learning: Dual Guidance for Utilization and Internalization
Fei Bai, Zhipeng Chen, Chuan Hao +6
Recently, reinforcement learning~(RL) has become an important approach for improving the capabilities of large language models~(LLMs). In particular, reinforcement learning from ve…
CGSPG: Confidence-calibrated Group Sequence Policy Gradient towards Self-aware Reasoning
Haotian Liu, Shuo Wang, Hongteng Xu
Reinforcement Learning (RL) methods, exemplified by Group Relative Policy Optimization (GRPO) and its variants, play a central role in developing reasoning models. However, these m…
MoORE: SVD-based Model MoE-ization for Conflict- and Oblivion-Resistant Multi-Task Adaptation
Shen Yuan, Yin Zheng, Taifeng Wang +2
Adapting large-scale foundation models in multi-task scenarios often suffers from task conflict and oblivion. To mitigate such issues, we propose a novel ''model MoE-ization'' stra…
Towards Better Multi-head Attention via Channel-wise Sample Permutation
Shen Yuan, Hongteng Xu
Transformer plays a central role in many fundamental deep learning models, e.g., the ViT in computer vision and the BERT and GPT in natural language processing, whose effectiveness…