6 citations · 16 across the 14 of their papers we have counts for
5 papers · 1 filter
Let Me Speak Freely? A Study on the Impact of Format Restrictions on Performance of Large Language Models
Zhi Rui Tam, Cheng-Kuang Wu, Yi-Lin Tsai +3
Structured generation, the process of producing content in standardized formats like JSON and XML, is widely utilized in real-world applications to extract key output information f…
I Need Help! Evaluating LLM's Ability to Ask for Users' Support: A Case Study on Text-to-SQL Generation
Cheng-Kuang Wu, Zhi Rui Tam, Chao-Chung Wu +3
This study explores the proactive ability of LLMs to seek user support. We propose metrics to evaluate the trade-off between performance improvements and user burden, and investiga…
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.…
StreamBench: Towards Benchmarking Continuous Improvement of Language Agents
Cheng-Kuang Wu, Zhi Rui Tam, Chieh-Yen Lin +2
Recent works have shown that large language model (LLM) agents are able to improve themselves from experience, which is an important ability for continuous enhancement post-deploym…
Examining Forgetting in Continual Pre-training of Aligned Large Language Models
Chen-An Li, Hung-Yi Lee
Recent advances in Large Language Models (LLMs) have exhibited remarkable proficiency across various tasks. Given the potent applications of LLMs in numerous fields, there has been…