Author

Tian-Le Pu

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Book Open access Aug 2026

A Perturbation-Augmented Unsupervised Learning Framework for Integer Linear Programming

Integer linear programming (ILP) plays a pivotal role in combinatorial optimization, with applications ranging from logistics to scheduling. Recently, unsupervised learning has emerged as a promising paradigm for solving ILPs without costly labeled solutions. However, existing methods often converge prematurely to pola...

Yufan Deng, Tian-Le Pu, Zhijing Hu et al. · Proceedings of the 32nd ACM... · 0 citations

Conference Aug 2026

Dual-Side Verification for Trustworthy LLM-Based Constrained Resource-Task Assignment Modeling

Constrained resource-task assignment(RTA) is a foundational problem in operations research and engineering decision support. Turning a natural-language assignment description into a correct optimization model and executable solver code requires expertise in both application semantics and mathematical programming. Large...

Bing-Xu Zhang, Tian-Le Pu, Long-Fei Zhang et al. · 2026 12th International Conf... · 0 citations

Preprint Aug 2026

Right Answer, Wrong Method: Shortcut Hacking Misleads the Evaluation of LLM Reasoning on Frontier Science Benchmarks

Solution Hacking is identified, a failure mode in which an LLM reaches the correct answer through invalid shortcuts, such as numerical search, enumeration, guessing, or answer-first verification, without providing a valid task-targeted derivation.

Xuanhua Ren, Weiqi Zhai, Tianle Pu et al. · 0 citations