Xing Chen
2025
Graph-Reward-SQL: Execution-Free Reinforcement Learning for Text-to-SQL via Graph Matching and Stepwise Reward
Han Weng
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Puzhen Wu
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Cui Longjie
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Yi Zhan
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Boyi Liu
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Yuanfeng Song
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Dun Zeng
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Yingxiang Yang
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Qianru Zhang
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Dong Huang
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Xiaoming Yin
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Yang Sun
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Xing Chen
Findings of the Association for Computational Linguistics: EMNLP 2025
Reinforcement learning (RL) has been widely adopted to enhance the performance of large language models (LLMs) on Text-to-SQL tasks. However, existing methods often rely on execution-based or LLM-based Bradley–Terry reward models. The former suffers from high execution latency caused by repeated database calls, whereas the latter imposes substantial GPU memory overhead, both of which significantly hinder the efficiency and scalability of RL pipelines. To this end, we propose a novel reward model framework for RL-based Text-to-SQL named Graph-Reward-SQL, which employs the GMNScore outcome reward model. We leverage SQL graph representations to provide accurate reward signals while significantly reducing time cost and GPU memory usage. Building on this foundation, we further introduce StepRTM, a stepwise reward model that provides intermediate supervision over Common Table Expression (CTE) subqueries. This encourages both functional correctness and readability of SQL. Extensive comparative and ablation experiments on standard benchmarks, including Spider and BIRD, demonstrate that our method consistently outperforms existing reward models.
2022
A Corpus-based Study of Corporate Image Represented in Corporate Social Responsibility Report: A Case Study of China Mobile and Vodafone
Xing Chen
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Liang Xu
Proceedings of the First Computing Social Responsibility Workshop within the 13th Language Resources and Evaluation Conference
By examination of the high-frequency nouns, verbs, and keywords, the present study probes into the similarities and differences of corporate images represented in Corporate Social Responsibility (CSR) reports of China Mobile and Vodafone. The results suggest that: 1) both China Mobile and Vodafone prefer using some positive words, like improve, support and service to shape a positive, approachable and easy-going corporate image, and an image of prioritizing the environmental sustainability and the well-being of people; 2) CSR reports of China Mobile contain the keywords poverty and alleviation, which means China Mobile is pragmatic, collaborative and active to assume the responsibility for social events; 3) CSR reports of Vodafone contain keywords like privacy, women and global as well as some other countries, which shows Vodafone is enterprising, globalized and attentive to the development of women; 4) these differences might be related to the ideology and social culture of Chinese and British companies. This study may contribute to understanding the function of CSR report and offer helpful implications for broadening the research of corporate image.