2025 ACL ACL 2025

HITSZ-HLT at SemEval-2025 Task 8: Multi-turn Interactive Code Generation for Question Answering on Tabular Data

Abstract

AbstractThis paper introduces the system developed by the HITSZ-HLT team for SemEval-2025 Task 8: DataBench, Question-Answering over Tabular Data.The primary objective of Table Question Answering (TableQA) is to provide accurate answers to user queries by interpreting and understanding tabular data. To address this, we propose the Multi-turn Interactive Code GeneratiOn(MICO) framework. Specifically, MICO employs code generation as proxy task for TableQA and integrates feedback from the execution of the generated code via multi-turn dialogue process, thereby guiding the model towards self-correction.Experimental results demonstrate the effectiveness of our framework, achieving notable performance with a rank of 4/38 on the DataBench and 5/38 on the DataBench lite.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Natural Language Processing
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio