3 papers
cs.CL2024
TARGA: Targeted Synthetic Data Generation for Practical Reasoning over Structured Data
Xiang Huang, Jiayu Shen, Shanshan Huang +3
Semantic parsing, which converts natural language questions into logic forms, plays a crucial role in reasoning within structured environments. However, existing methods encounter…
cs.CL2024
Call Me When Necessary: LLMs can Efficiently and Faithfully Reason over Structured Environments
Sitao Cheng, Ziyuan Zhuang, Yong Xu +9
Large Language Models (LLMs) have shown potential in reasoning over structured environments, e.g., knowledge graph and table. Such tasks typically require multi-hop reasoning, i.e.…
cs.CL2024
QueryAgent: A Reliable and Efficient Reasoning Framework with Environmental Feedback-based Self-Correction
Xiang Huang, Sitao Cheng, Shanshan Huang +4
Employing Large Language Models (LLMs) for semantic parsing has achieved remarkable success. However, we find existing methods fall short in terms of reliability and efficiency whe…