Shaoyang Guo 郭绍阳

Curriculum Vitae

Shaoyang Guo 郭绍阳

Physics undergraduate at Peking University (Class of 2027). Research intern at ByteDance Seed. Working on LLM/VLM post-training, RL/SFT, agents, benchmarking, and Physics of AI.

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Education

B.S. in Physics, Peking University (expected 2027). Admitted via PKU Excellence Program (CPhO Gold Medal). GPA 3.74/4.00, top 10% in the School of Physics. 141/149 credits by sophomore year including 3 graduate courses.

Peking University, School of Physics

B.S. in Physics, expected Jun 2027. GPA 3.74/4.00, top 10% in the School of Physics; completed 141/149 credits by sophomore year including 3 graduate courses.

National Scholarship (2024)

Ministry of Education, top 1% at Peking University.

Chinese Physics Olympiad Gold Medal

National rank #57 (2022). Admitted to PKU Physics via PKU Excellence Program.

NOIP First Prize (2020)

National Olympiad in Informatics in Provinces.

Research Experience

Jul 2025 – Present

Research Intern, VLM/LLM Post-Training

ByteDance Seed

Working on post-training and research automation for VLM/LLM systems, with emphasis on RL, SFT, mid-training, rollouts, data pipelines, and agent workflows.

  • Contributed to HiPhO-oriented RL, SFT, and mid-training work for Seed 2.0 models, improving reported Lite performance from 72.5 to 83.8.
  • Participated in mid-training runs at large compute scale and supported rollout pipelines for model improvement.
  • Built data and prompt pipelines for QA pairs, CoT compression, summaries, and SFT-to-RL transfer experiments.
  • Explored auto-research agent loops, adversarial pair agents, and agent-based research settings.
Feb 2025 – Sep 2025

Co-initiator & Co-first Author, PHYBench

Peking University, Eureka Lab

Co-initiated and co-led PHYBench, a physics perception and reasoning benchmark for LLMs.

  • Identified gaps in existing LLM physics evaluation and led the project from concept validation to a full data pipeline.
  • Organized 178 PKU students to build 500 high-quality original physics problems in 2 weeks.
  • Designed evaluation criteria and quality-control workflows for LLM physics reasoning.
  • Co-authored the arXiv preprint submitted to NeurIPS 2025.
Mar 2025 – Aug 2025

Research Assistant, VLA Survey

PsiRobot Lab, Peking University

Co-authored a survey on Vision-Language-Action models from an action-tokenization perspective.

  • Responsible for the Raw Action chapter; reviewed 30+ key papers on end-to-end VLA architectures.
  • Organized taxonomies for VLA model design and contributed to the arXiv preprint.

Skills

Programming

Shell, Python, PyTorch, Spark, C/C++, MATLAB

ML/AI

RL for LLMs including RLHF and BoN, SFT, mid-training, benchmarking, multi-agent systems

Physics

Comprehensive PKU physics training, with strengths in statistical analysis, computational physics, and experimental physics

Languages

Chinese (native), English (CET-6: 657, GRE: 150+170)

Research Interests & Publications

Focus Areas

  • LLM/VLM
  • RL/SFT/Agents
  • Benchmarking
  • Physics of AI

Publications