4 papers
Reverse Preference Optimization for Complex Instruction Following
Xiang Huang, Ting-En Lin, Feiteng Fang +5
Instruction following (IF) is a critical capability for large language models (LLMs). However, handling complex instructions with multiple constraints remains challenging. Previous…
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…
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…
MarkQA: A large scale KBQA dataset with numerical reasoning
Xiang Huang, Sitao Cheng, Yuheng Bao +2
While question answering over knowledge bases (KBQA) has shown progress in addressing factoid questions, KBQA with numerical reasoning remains relatively unexplored. In this paper,…