Can large language model (LLM) agents deliver expert-level operations research (OR) solutions directly from original client materials, without prior expert reformulation? Existing OR benchmarks typically begin with self-contained descriptions or predefined optimization tasks, underrepresenting the translation of origin...
Peisong Wang, Fei-Xue Liu, Yi-Ze Meng et al.· 0 citations
Tabular Anomaly Detection (TAD) plays a fundamental role in securing real-world applications. Despite rapid advances in TAD, the prohibitive cost of human-centric label annotation remains a primary bottleneck for large-scale production systems. To alleviate this bottleneck, we propose a novel ''coarse-to-fine'' label a...
Haihong Zhao, Aochuan Chen, Miao Peng et al.· Proceedings of the 32nd ACM...· 0 citations
$R^3$-Bench is introduced, which evaluates six-problem suites under shared budgets across mathematics, competitive programming, and abstract reasoning in tool-free and agentic settings, and exposes a persistent gap between demonstrated competence and shared-budget realization.
Peisong Wang, Zhiwei Ma, Bo-Wen Liu et al.· 0 citations
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