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20232026
most citedHow Can Recommender Systems Benefit from Large Language Models: A Survey

21 citations · 34 across the 17 of their papers we have counts for

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cs.SE2025★ 1 cited

ATGen: Adversarial Reinforcement Learning for Test Case Generation

Qingyao Li, Xinyi Dai, Weiwen Liu +5

Large Language Models (LLMs) excel at code generation, yet their outputs often contain subtle bugs, for which effective test cases are a critical bottleneck. Existing test generati…

cs.SE2025

Humanity's Last Code Exam: Can Advanced LLMs Conquer Human's Hardest Code Competition?

Xiangyang Li, Xiaopeng Li, Kuicai Dong +7

Code generation is a core capability of large language models (LLMs), yet mainstream benchmarks (e.g., APPs and LiveCodeBench) contain questions with medium-level difficulty and po…