Showing cs.CLShow all
3 papers · 1 filter
cs.CL2025
AdaSearch: Balancing Parametric Knowledge and Search in Large Language Models via Reinforcement Learning
Tzu-Han Lin, Wei-Lin Chen, Chen-An Li +3
Equipping large language models (LLMs) with search engines via reinforcement learning (RL) has emerged as an effective approach for building search agents. However, overreliance on…
cs.CL2025
Transferring Textual Preferences to Vision-Language Understanding through Model Merging
Chen-An Li, Tzu-Han Lin, Yun-Nung Chen +1
Large vision-language models (LVLMs) perform outstandingly across various multimodal tasks. However, their ability to evaluate generated content remains limited, and training visio…
cs.CL2024
DogeRM: Equipping Reward Models with Domain Knowledge through Model Merging
Tzu-Han Lin, Chen-An Li, Hung-yi Lee +1
Reinforcement learning from human feedback (RLHF) is a popular strategy for aligning large language models (LLMs) with desired behaviors. Reward modeling is a crucial step in RLHF.…