activity
20202026
most citedLEGO-Prover: Neural Theorem Proving with Growing Libraries

9 citations · 30 across the 30 of their papers we have counts for

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Showing 2025Show all

9 papers · 1 filter

cs.AI2025

Aligning Perception, Reasoning, Modeling and Interaction: A Survey on Physical AI

Kun Xiang, Terry Jingchen Zhang, Yinya Huang +13

The rapid advancement of embodied intelligence and world models has intensified efforts to integrate physical laws into AI systems, yet physical perception and symbolic physics rea…

cs.LG2025

Critique to Verify: Accurate and Honest Test-Time Scaling with RL-Trained Verifiers

Zhicheng Yang, Zhijiang Guo, Yinya Huang +4

Test-time scaling via solution sampling and aggregation has become a key paradigm for improving the reasoning performance of Large Language Models (LLMs). While reward model select…

cs.AI2025

Test of Time: Rethinking Temporal Signal of Benchmark Contamination

Terry Jingchen Zhang, Gopal Dev, Ning Wang +8

Post-cutoff performance decay of LLMs has been widely interpreted as a temporal signal for benchmark contamination, where public information released before the training cutoff may…

cs.LO2025

Lean Meets Theoretical Computer Science: Scalable Synthesis of Theorem Proving Challenges in Formal-Informal Pairs

Terry Jingchen Zhang, Wenyuan Jiang, Rongchuan Liu +6

Formal theorem proving (FTP) has emerged as a critical foundation for evaluating the reasoning capabilities of large language models, enabling automated verification of mathematica…

cs.LG2025

Depth-Breadth Synergy in RLVR: Unlocking LLM Reasoning Gains with Adaptive Exploration

Zhicheng Yang, Zhijiang Guo, Yinya Huang +6

Reinforcement Learning with Verifiable Reward (RLVR) is a powerful method for enhancing the reasoning abilities of Large Language Models, but its full potential is limited by a lac…

cs.LG2025

TreeRPO: Tree Relative Policy Optimization

Zhicheng Yang, Zhijiang Guo, Yinya Huang +3

Large Language Models (LLMs) have shown remarkable reasoning capabilities through Reinforcement Learning with Verifiable Rewards (RLVR) methods. However, a key limitation of existi…

cs.AI2025★ 1 cited

ORMind: A Cognitive-Inspired End-to-End Reasoning Framework for Operations Research

Zhiyuan Wang, Bokui Chen, Yinya Huang +4

Operations research (OR) is widely deployed to solve critical decision-making problems with complex objectives and constraints, impacting manufacturing, logistics, finance, and hea…

cs.AI2025

SeePhys: Does Seeing Help Thinking? -- Benchmarking Vision-Based Physics Reasoning

Kun Xiang, Heng Li, Terry Jingchen Zhang +11

We present SeePhys, a large-scale multimodal benchmark for LLM reasoning grounded in physics questions ranging from middle school to PhD qualifying exams. The benchmark covers 7 fu…

cs.CL2025

LEXam: Benchmarking Legal Reasoning on 340 Law Exams

Yu Fan, Jingwei Ni, Jakob Merane +14

Long-form legal reasoning remains a key challenge for large language models (LLMs) in spite of recent advances in test-time scaling. To address this, we introduce LEXam, a novel be…