15 citations · 36 across the 29 of their papers we have counts for
4 papers · 1 filter
Deliberate Evolution: Agentic Reasoning for Sample-Efficient Symbolic Regression with LLMs
Xinyu Pang, Zhanke Zhou, Xuan Li +5
Symbolic regression (SR) discovers compact mathematical expressions from data, yet recent LLM-based evolutionary methods remain sample-inefficient because they rely mainly on scala…
Eliciting Causal Abilities in Large Language Models for Reasoning Tasks
Yajing Wang, Zongwei Luo, Jingzhe Wang +3
Prompt optimization automatically refines prompting expressions, unlocking the full potential of LLMs in downstream tasks. However, current prompt optimization methods are costly t…
Physics Reasoner: Knowledge-Augmented Reasoning for Solving Physics Problems with Large Language Models
Xinyu Pang, Ruixin Hong, Zhanke Zhou +5
Physics problems constitute a significant aspect of reasoning, necessitating complicated reasoning ability and abundant physics knowledge. However, existing large language models (…
Can Language Models Perform Robust Reasoning in Chain-of-thought Prompting with Noisy Rationales?
Zhanke Zhou, Rong Tao, Jianing Zhu +3
This paper investigates an under-explored challenge in large language models (LLMs): chain-of-thought prompting with noisy rationales, which include irrelevant or inaccurate reason…