6 papers · 1 filter
AgentExpt: Automating AI Experiment Design with LLM-based Resource Retrieval Agent
Yu Li, Lehui Li, Lin Chen +3
Large language model agents are becoming increasingly capable at web-centric tasks such as information retrieval, complex reasoning. These emerging capabilities have given rise to…
Route-and-Reason: Scaling Large Language Model Reasoning with Reinforced Model Router
Chenyang Shao, Xinyang Liu, Yutang Lin +2
Chain-of-thought has been proven essential for enhancing the complex reasoning abilities of Large Language Models (LLMs), but it also leads to high computational costs. Recent adva…
Diffuse Thinking: Exploring Diffusion Language Models as Efficient Thought Proposers for Reasoning
Chenyang Shao, Sijian Ren, Fengli Xu +1
In recent years, large language models (LLMs) have witnessed remarkable advancements, with the test-time scaling law consistently enhancing the reasoning capabilities. Through syst…
Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models
Peijie Liu, Fengli Xu, Yong Li
Chain-of-Thought (CoT) technique has proven effective in improving the performance of large language models (LLMs) on complex reasoning tasks. However, the performance gains are in…
AgentSquare: Automatic LLM Agent Search in Modular Design Space
Yu Shang, Yu Li, Keyu Zhao +4
Recent advancements in Large Language Models (LLMs) have led to a rapid growth of agentic systems capable of handling a wide range of complex tasks. However, current research large…
Synergy-of-Thoughts: Eliciting Efficient Reasoning in Hybrid Language Models
Yu Shang, Yu Li, Fengli Xu +1
Large language models (LLMs) have shown impressive emergent abilities in a wide range of tasks, but the associated expensive API cost greatly limits the real application. Previous…