1 citations · 1 across the 17 of their papers we have counts for
11 papers · 1 filter
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…
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…
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…
A Unified Framework for Formalizing Matrix Decomposition Proofs
Wanli Ma, Zichen Wang, Zaiwen Wen
Existence proofs for many matrix decompositions share a recursive routine: a local transformation prepares the matrix, a slice is selected, a recursive solution is obtained, and th…
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…
Nyström Approximation on Manifolds
Hantao Nie, Bin Gao, Andi Han +3
Computations on a manifold often involve constructing an operator on the tangent space and computing its inverse, which can be time-consuming in many applications. In order to redu…
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…
OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving
Chenyi Li, Yanchen Nie, Zhenyu Ming +3
Recent advances in formal theorem proving have focused on Olympiad-level mathematics, leaving undergraduate domains largely unexplored. Optimization, fundamental to machine learnin…
Learning to Solve the Quadratic Assignment Problem with Warm-Started MCMC Finetuning
Yicheng Pan, Ruisong Zhou, Haijun Zou +2
The quadratic assignment problem (QAP) is a fundamental NP-hard task that poses significant challenges for both traditional heuristics and modern learning-based solvers. Existing Q…
A Learning Method with Gap-Aware Generation for Heterogeneous DAG Scheduling
Ruisong Zhou, Haijun Zou, Li Zhou +2
Efficient scheduling of directed acyclic graphs (DAGs) is a core problem in large-scale data-intensive computing systems, where query plans, data-processing workloads, and computat…
Construction-Verification: A Benchmark for Applied Mathematics in Lean 4
Bowen Yang, Yi Yuan, Chenyi Li +5
Recent advances in large language models have demonstrated impressive capabilities in mathematical formalization. However, existing benchmarks focus on logical verification of decl…