2 citations · 3 across the 11 of their papers we have counts for
4 papers · 1 filter
Think Thrice Before You Act: Progressive Thought Refinement in Large Language Models
Chengyu Du, Jinyi Han, Yizhou Ying +9
Recent advancements in large language models (LLMs) have demonstrated that progressive refinement, rather than providing a single answer, results in more accurate and thoughtful ou…
SED: Self-Evaluation Decoding Enhances Large Language Models for Better Generation
Ziqin Luo, Haixia Han, Haokun Zhao +6
Existing Large Language Models (LLMs) generate text through unidirectional autoregressive decoding methods to respond to various user queries. These methods tend to consider token…
Enhancing Confidence Expression in Large Language Models Through Learning from Past Experience
Haixia Han, Tingyun Li, Shisong Chen +5
Large Language Models (LLMs) have exhibited remarkable performance across various downstream tasks, but they may generate inaccurate or false information with a confident tone. One…
CEM: A Data-Efficient Method for Large Language Models to Continue Evolving From Mistakes
Haokun Zhao, Haixia Han, Jie Shi +3
As world knowledge advances and new task schemas emerge, Continual Learning (CL) becomes essential for keeping Large Language Models (LLMs) current and addressing their shortcoming…