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Pengcheng Wang

University of Illinois, Urbana Champaign

4 papers hereh-index 3259 citations7 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • cs.AI1
  • cs.CL1
affiliations
  • University of Illinois, Urbana Champaign
HomepageORCID 0000-0002-4012-9293
same name
  • Pengcheng Wang — 9 papers, h 2
  • Pengcheng Wang — 3 papers, h 1
  • Pengcheng Wang — 3 papers, h 4
  • Pengcheng Wang — 3 papers, h 2
  • Pengcheng Wang — 3 papers, h 2
  • Pengcheng Wang — 3 papers, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

cs.LG2026

Diffusion-Proof: Recipe for Formal Theorem Proving Beyond Auto-Regressive Generation

Ruida Wang, Rui Pan, Pengcheng Wang +2

Enhancing the formal math reasoning capabilities of Large Language Models (LLMs) has become a key focus in both mathematical and computer science communities in recent years. While…

cs.AI2026

Lean4Agent: Formal Modeling and Verification for Agent Workflow and Trajectory

Ruida Wang, Jerry Huang, Pengcheng Wang +3

Equipping Large Language Models (LLMs) to execute reliable multi-step workflows has become a central challenge in artificial intelligence. Despite recent advances in LLMs' agentic…

cs.CL2026

AgentSPEX: An Agent SPecification and EXecution Language

Pengcheng Wang, Jerry Huang, Jiarui Yao +7

Language-model agent systems commonly rely on reactive prompting, in which a single instruction guides the model through an open-ended sequence of reasoning and tool-use steps, lea…

cs.LG2025

Entropy-Regularized Process Reward Model

Hanning Zhang, Pengcheng Wang, Shizhe Diao +6

Large language models (LLMs) have shown promise in performing complex multi-step reasoning, yet they continue to struggle with mathematical reasoning, often making systematic error…

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