Zhicheng Yang
PhD Candidate in Large Language Model Reasoning
I'm pursuing a PhD degree. I work on reasoning-centric large language models, with current interests in solve-and-verify paradigms, reasoning data synthesis, and test-time scaling. My recent work focuses on advanced expert-level mathematical reasoning, verification, efficiency & readability CoT, and agentic reasoning.

Research Interests
Background
Experience
- LLM Research Intern, ByteDance Seed
- LLM Research Intern, Huawei Noah's Ark Lab
- Recommender System Intern, ByteDance Douyin
Education
- 2020 - 2023: Master in Pattern Recognition and Intelligent Systems, Sun Yat-sen University
- 2016 - 2020: B.Sc. in Computer Science and Technology, Sun Yat-sen University
Honors & Awards
- National First Prize, Contemporary Undergraduate Mathematical Contest in Modeling
- First Prize Scholarship, Sun Yat-sen University
Professional Service
- Area Chair, ACL Rolling Review (ARR), January 2026
- Reviewer for ICML, NeurIPS, ICLR, ACL, EMNLP, NAACL, and TNNLS
News
Two papers were accepted to EMNLP 2025.
Co-organizing the 2nd AI4MATH Workshop at ICML 2025.
One paper was accepted to ICLR 2025.
Served as challenge lead organizer for Automated Optimization Problem-Solving with Code at ICML 2024.
Preprints
Current directions in efficient and verifiable LLM reasoning.
Preprint
🔥 Accordion-Thinking: Self-Regulated Step Summaries for Efficient and Readable LLM Reasoning
Preprint
🔥🔥 Depth-Breadth Synergy in RLVR: Unlocking LLM Reasoning Gains with Adaptive Exploration
Preprint
TreeRPO: Tree Relative Policy Optimization
Preprint
Critique to Verify: Accurate and Honest Test-Time Scaling with RL-Trained Verifiers
Selected Papers
Representative publications in reasoning, mathematical intelligence, and verification.
ICLR 2025
OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modeling
CVPR 2026
CARE What Fails: Contrastive Anchored-REflection for Verifiable Multimodal Reasoning
NeurIPS 2024
Proving Theorems Recursively
Findings of EMNLP 2024
AlignedCoT: Prompting Large Language Models via Native-Speaking Demonstrations
ACL 2024
CLOMO: Counterfactual Logical Modification with Large Language Models
Findings of NAACL 2024
ATG: Benchmarking Automated Theorem Generation for Generative Language Models
Findings of EMNLP 2022
LogicSolver: Towards Interpretable Math Word Problem Solving with Logical Prompt-Enhanced Learning
Findings of NAACL 2022
Unbiased Math Word Problems Benchmark for Mitigating Solving Bias
TNNLS 2023