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cs.CL2026

Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQL

Hanqing Wang, Yongdong Chi, Jian Yang +4

While Large Language Models (LLMs) have achieved remarkable success in Text-to-SQL tasks, their deployment in real-world environments is hindered by latent reliability issues. Iden…

cs.CL2026

MARDoc: A Memory-Aware Refinement Agent Framework for Multimodal Long Document QA

Kaifeng Chen, Hongtao Liu, Qiyao Peng +4

Iterative retrieval-reasoning agents have recently shown promise for multimodal long-document question answering. However, most existing systems maintain a single growing context t…

cs.CL2026

Rethinking Stepwise Model Routing: A Cost-Efficient Table Reasoning Perspective

Shenghao Ye, Yuxiang Wang, Yu Guo +3

Large Reasoning Models (LRMs) achieve strong performance on table reasoning tasks but incur substantial inference cost due to long reasoning traces. Stepwise model routing mitigate…

cs.CL2025

Pi-SQL: Enhancing Text-to-SQL with Fine-Grained Guidance from Pivot Programming Languages

Yongdong chi, Hanqing Wang, Zonghan Yang +4

Text-to-SQL transforms the user queries from natural language to executable SQL programs, enabling non-experts to interact with complex databases. Existing prompt-based methods cra…

cs.CL2025

SQLForge: Synthesizing Reliable and Diverse Data to Enhance Text-to-SQL Reasoning in LLMs

Yu Guo, Dong Jin, Shenghao Ye +3

Large Language models (LLMs) have demonstrated significant potential in text-to-SQL reasoning tasks, yet a substantial performance gap persists between existing open-source models…