most citedOptMATH: A Scalable Bidirectional Data Synthesis Framework for Optimization Modeling

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cs.AI2026

FaithSieve: Fine-Grained Evaluation of Math Proofs with Faithful Formal Evidence

Ziyu Wang, Qiming Dai, Yishan Wu +1

Large language models can now generate complex, multi-step mathematical proofs, but reliably determining their correctness and localizing early logical errors remains a critical ch…

cs.AI2026

ReasFlow: Assisting Reasoning-Centric Scientific Discovery in Applied Mathematics via a Knowledge-Based Multi-Agent System

Yutong He, Daibo Li, Guohong Li +15

Recent advances in Large Language Models have fueled autonomous AI agents capable of tackling complex scientific tasks, yet existing automated research systems remain predominantly…

cs.AI2026

MECA: A Mechanism-Centered Agent for Constructing Well-Specified and Valuable Mathematical Conjectures

Wentao Long, Yunfei Zhang, Chenyi Li +1

Automatically constructing well-specified and valuable mathematical conjectures remains a central challenge in AI-assisted mathematical discovery. Many existing open problems and c…

cs.AI2026

CAM-Bench: A Benchmark for Computational and Applied Mathematics in Lean

Wentao Long, Yunfei Zhang, Chenyi Li +3

Formal theorem-proving benchmarks enable mechanically verifiable evaluation of mathematical reasoning in large language models. However, existing benchmarks mainly focus on Olympia…

cs.AI2026

MM-OptBench: A Solver-Grounded Benchmark for Multimodal Optimization Modeling

Zhong Li, Qi Huang, Yuxuan Zhu +6

Optimization modeling translates real decision-making problems into mathematical optimization models and solver-executable implementations. Although language models are increasingl…

cs.AI2025

SITA: A Framework for Structure-to-Instance Theorem Autoformalization

Chenyi Li, Wanli Ma, Zichen Wang +1

While large language models (LLMs) have shown progress in mathematical reasoning, they still face challenges in formalizing theorems that arise from instantiating abstract structur…