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Conference Aug 2026

A Dynamic Evaluation Framework for LLM Instruction Following: Multi-dimensional Verification and Iterative Feedback

Accurately evaluating the instruction-following ability of Large Language Models (LLMs) is crucial for their practical deployment. Existing evaluation methods mainly rely on static assessment of single-pass generations, making it difficult to comprehensively measure instruction-following performance or models’ capabili...

Ya-Chao Fu, Qu-Fei Zhang, Meng-Na Zhu et al. · 0 citations
Conference Aug 2026

A Template-Driven Multi-Source Benchmark Generation Method for Heterogeneous Data Lakes

Large language models (LLMs) have rapidly advanced natural-language-to-query (Text-to-Query) capabilities, yet existing public benchmarks remain confined to single database paradigms such as Text-to-SQL or Text-to-KG. They do not capture real-world settings where relational databases, graph databases, document database...

Guo-Shen Li, Hang Zhang, Ying-Jun Liu et al. · 0 citations

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