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cs.CL2025
DI-BENCH: Benchmarking Large Language Models on Dependency Inference with Testable Repositories at Scale
Linghao Zhang, Junhao Wang, Shilin He +13
Large Language Models have advanced automated software development, however, it remains a challenge to correctly infer dependencies, namely, identifying the internal components and…
cs.CL2023★ 1 cited
Rethinking the Instruction Quality: LIFT is What You Need
Yang Xu, Yongqiang Yao, Yufan Huang +4
Instruction tuning, a specialized technique to enhance large language model (LLM) performance via instruction datasets, relies heavily on the quality of employed data. Existing qua…