Y
Scholar

Yiming Huang

Google Scholar ID: L8E-ccakgcQC
UCSD
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Resume (English only)
Academic Achievements
  • Publications:
  • - GATE: Graph-based Adaptive Tool Evolution Across Diverse Tasks
  • - Key-Point-Driven Data Synthesis with its Enhancement on Mathematical Reasoning
  • - DA-Code: Agent Data Science Code Generation Benchmark for Large Language Models
  • - Competition-level Problems Are Effective LLM Evaluators
  • - S3Eval: A Synthetic, Scalable, Systematic Evaluation Suite for Large Language Models
  • - S3HQA: A Three-Stage Approach for Multi-hop Text-Table Hybrid Question Answering
  • - ADFA: Attention-Augmented Differentiable Top-k Feature Adaptation for Unsupervised Medical Anomaly Detection
  • - Spatial and Planar Consistency for Semi-Supervised Volumetric Medical Image Segmentation
  • Awards:
  • - UCSD Jacobs School of Engineering Fellowship, 2025
  • - USTB Principal Medal (10 out of all undergraduate graduates, highest honor of undergraduate student), 2023
  • - Beijing Outstanding Graduate Awards (top 1% in Academics), 2023
  • - National Scholarship (Top 0.2% nationwide), 2022
  • - National Scholarship (Top 0.2% nationwide), 2021
  • - National Scholarship (Top 0.2% nationwide), 2020
Research Experience
  • Worked as a research intern at TikTok, collaborating with Dr. Qian Liu. Previously spent time at Microsoft Research Asia, working with Dr. Xiao Liu, Dr. Yeyun Gong, and Dr. Weizhu Chen.
Education
  • PhD student at UC San Diego, advised by Prof. Jingbo Shang
Background
  • Research interests include evaluating and enhancing the reasoning capabilities of large language models, particularly in code, math, and agent tasks; exploring data-centric methods to improve learning efficiency and adaptability.
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