Author

D. Song

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#artificial intelligence Preprint Oct 2026

TestJack: Should you trust the results in coding benchmarks? Agentic Coding Benchmarks Auditing via Evaluator Evolution

Large language model (LLM) agents are rapidly reshaping software engineering, accompanied by an explosion of new code benchmarks. Yet nearly all existing benchmarks still rely on the same decades-old criterion: a solution is correct if it passes a fixed set of unit tests. Such tests are often insufficient: they check o...

Shuang-Jie Yao, Hao Wang, Koushik Sen et al. · 0 citations

#artificial intelligence Jun 2026

ChainWorld: Composing Long-Horizon Desktop Workloads from Atomic OSWorld Tasks

ChainWorld, which composes atomic OSWorld tasks into long horizon desktop workloads through directional compatibility search while preserving the source evaluators, is studied, which contains 347 chains of length two to four and compares two renderings of the same task sequence.

Vincent Siu, Manasi Sharma, D. Song et al. · arXiv.org · 0 citations