2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.DB2026
SQLAgent: Learning to Explore Before Generating as a Data Engineer
Wenjia Jiang, Yiwei Wang, Boyan Han +2
Large Language Models have recently shown impressive capabilities in reasoning and code generation, making them promising tools for natural language interfaces to relational databa…
cs.CL2024
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…
cs.CL2024★ 2 cited
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 (…