6 papers
Small Language Model Helps Resolve Semantic Ambiguity of LLM Prompt
Zhenzhen Huang, Chaoning Zhang, Fachrina Dewi Puspitasari +4
Large language models (LLMs) are increasingly utilized in various complex reasoning tasks due to their excellent instruction following capability. However, the model's performance…
Lightweight LLM Agent Memory with Small Language Models
Jiaquan Zhang, Chaoning Zhang, Shuxu Chen +9
Although LLM agents can leverage tools for complex tasks, they still need memory to maintain cross-turn consistency and accumulate reusable information in long-horizon interactions…
Agent-GWO: Collaborative Agents for Dynamic Prompt Optimization in Large Language Models
Xudong Wang, Chaoning Zhang, Chenghao Li +10
Large Language Models (LLMs) have demonstrated strong capabilities in complex reasoning tasks, while recent prompting strategies such as Chain-of-Thought (CoT) have further elevate…
Learning Global Hypothesis Space for Enhancing Synergistic Reasoning Chain
Jiaquan Zhang, Chaoning Zhang, Shuxu Chen +9
Chain-of-Thought (CoT) has been shown to significantly improve the reasoning accuracy of large language models (LLMs) on complex tasks. However, due to the autoregressive, step-by-…
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…
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…