Papers with error localization
SHARE: An SLM-based Hierarchical Action CorREction Assistant for Text-to-SQL (2025.acl-long)
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| Challenge: | Existing approaches to self-correct text-to-SQL fail to demonstrate underlying reasoning path . authors propose **SHARE**, a self-revolution assistant for text-based error correction . |
| Approach: | They propose a "SHARE" assistant that enables LLMs to perform more precise error localization and efficient correction. |
| Outcome: | The proposed assistant performs more precise error localization and efficient correction for monolithic SQL queries. |
ReflectEvo: Improving Meta Introspection of Small LLMs by Learning Self-Reflection (2025.findings-acl)
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Jiaqi Li, Xinyi Dong, Yang Liu, Zhizhuo Yang, Quansen Wang, Xiaobo Wang, Song-Chun Zhu, Zixia Jia, Zilong Zheng
| Challenge: | ReflectEvo-460k is a large-scale, comprehensive, self-generated reflection dataset with broadened instructions and diverse multi-domain tasks. |
| Approach: | They propose a pipeline that iteratively generates self-reflection for self-training and a large-scale reflection dataset with broadened instructions and diverse multi-domain tasks. |
| Outcome: | The proposed pipeline improves Llama-3 reasoning ability by up to 71.2% and Mistral by upto 44.4%. |
VEHME: A Vision-Language Model For Evaluating Handwritten Mathematics Expressions (2025.emnlp-main)
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| Challenge: | VEHME is a vision language model for assessing handwritten math answers . traditional methods of assessing student work are limited by time constraints, class sizes and cognitive load . |
| Approach: | They propose a Vision-Language Model for Evaluating Handwritten Mathematics Expressions to assess handwritten math responses with high accuracy and interpretable reasoning traces. |
| Outcome: | VEHME achieves state-of-the-art performance among open-source models and approaches accuracy of proprietary systems. |