5 papers
Understanding Chain-of-Thought in Large Language Models via Topological Data Analysis
Chenghao Li, Chaoning Zhang, Yi Lu +10
With the development of large language models (LLMs), particularly with the introduction of the long reasoning chain technique, the reasoning ability of LLMs in complex problem-sol…
Text summarization via global structure awareness
Jiaquan Zhang, Chaoning Zhang, Shuxu Chen +9
Text summarization is a fundamental task in natural language processing (NLP), and the information explosion has made long-document processing increasingly demanding, making summar…
Syzygy of Thoughts: Improving LLM CoT with the Minimal Free Resolution
Chenghao Li, Chaoning Zhang, Yi Lu +7
Chain-of-Thought (CoT) prompting enhances the reasoning of large language models (LLMs) by decomposing problems into sequential steps, mimicking human logic and reducing errors. Ho…
Re-Initialization Token Learning for Tool-Augmented Large Language Models
Chenghao Li, Liu Liu, Baosheng Yu +2
Large language models have demonstrated exceptional performance, yet struggle with complex tasks such as numerical reasoning, plan generation. Integrating external tools, such as c…
Interpreting and Improving Attention From the Perspective of Large Kernel Convolution
Chenghao Li, Chaoning Zhang, Boheng Zeng +7
Attention mechanisms have significantly advanced visual models by capturing global context effectively. However, their reliance on large-scale datasets and substantial computationa…