Portrait
Yuwei Zhang
Ph.D. Student, Halıcıoğlu Data Science Institute, UC San Diego
About Me

I am a Ph.D. student at the Halıcıoğlu Data Science Institute, UC San Diego, advised by Prof. Jingbo Shang. My research focuses on LLM post-training, continual adaptation, and memory.

I am especially interested in how language models can improve after pretraining: learning from limited task data, rare success signals, long-horizon feedback, and persistent context while retaining prior knowledge. My recent work studies knowledge injection, on-policy self-distillation / reinforcement learning, and memory-based context management.

Beyond research, I am passionate about sports, especially hiking, basketball and motor racing.

I want to express my sincere gratitude to my advisors, collaborators, and mentors for their invaluable guidance and support throughout my research and life.

Curriculum Vitae
Education
  • University of California San Diego
    Halıcıoğlu Data Science Institute
    Ph.D. in Data Science
    2023 - present
  • University of California San Diego
    Electrical Engineering
    M.S. in Electrical Engineering, Machine Learning & Data Science
    2021 - 2023
  • Nankai University
    Physics
    B.S. in Physics
    2016 - 2020
Experience
  • Google DeepMind
    Research Scientist Intern
    Summer 2026
  • Amazon Rufus (Foundation Models Team)
    Applied Scientist Intern
    Summer 2025 - Summer 2026
  • AMD Research
    Research Scientist Intern
    Spring 2025
  • Tencent AI Lab
    Research Scientist Intern
    Summer 2024
  • Amazon AWS
    Applied Scientist Intern
    Summer 2023
News
2026
We released the paper, code and blog for RESD, our work on on-policy self-distillation.
May 12
Our work on agent context management CoMem was accepted to ICML 2026.
May 01
Our work on knowledge injection WikiDYK was accepted to ACL 2026 as an oral presentation.
Apr 07
Selected Publications (view all )
CoMem: Context Management with A Decoupled Long-Context Model
CoMem: Context Management with A Decoupled Long-Context Model

Yuwei Zhang, Chengyu Dong, Shuowei Jin, Changlong Yu, Hejie Cui, Hongye Jin, Xinyang Zhang, Hamed Bonab, Colin Lockard, Jianshu Chen, Zhenyu Shi, Jingbo Shang, Xian Li, Bing Yin

ICML 2026

CoMem decouples agent reasoning from memory summarization so long-horizon agents can preserve most long-context performance while reducing latency through asynchronous context management.

CoMem: Context Management with A Decoupled Long-Context Model

Yuwei Zhang, Chengyu Dong, Shuowei Jin, Changlong Yu, Hejie Cui, Hongye Jin, Xinyang Zhang, Hamed Bonab, Colin Lockard, Jianshu Chen, Zhenyu Shi, Jingbo Shang, Xian Li, Bing Yin

ICML 2026

CoMem decouples agent reasoning from memory summarization so long-horizon agents can preserve most long-context performance while reducing latency through asynchronous context management.

Learning with Rare Success but Rich Feedback via Reflection-Enhanced Self-Distillation
Learning with Rare Success but Rich Feedback via Reflection-Enhanced Self-Distillation

Yuwei Zhang, Sha Li, Changlong Yu, Qin Lu, Shuowei Jin, Chengyu Dong, Haoran Liu, Ilgee Hong, Xintong Li, Zhenyu Shi, Bing Yin, Jingbo Shang

Preprint 2026

RESD turns failed rollouts into reflection-based supervision and reusable playbook knowledge, letting models improve efficiently even when successful rollouts are rare.

Learning with Rare Success but Rich Feedback via Reflection-Enhanced Self-Distillation

Yuwei Zhang, Sha Li, Changlong Yu, Qin Lu, Shuowei Jin, Chengyu Dong, Haoran Liu, Ilgee Hong, Xintong Li, Zhenyu Shi, Bing Yin, Jingbo Shang

Preprint 2026

RESD turns failed rollouts into reflection-based supervision and reusable playbook knowledge, letting models improve efficiently even when successful rollouts are rare.

Bidirectional LMs are Better Knowledge Memorizers? A Benchmark for Real-world Knowledge Injection
Bidirectional LMs are Better Knowledge Memorizers? A Benchmark for Real-world Knowledge Injection

Yuwei Zhang, Wenhao Yu, Shangbin Feng, Yifan Zhu, Letian Peng, Jayanth Srinivasa, Gaowen Liu, Jingbo Shang

ACL 2026 Oral

WikiDYK benchmarks real-world knowledge injection from fresh Wikipedia facts and shows bidirectional language models memorize injected knowledge more reliably than causal LMs.

Bidirectional LMs are Better Knowledge Memorizers? A Benchmark for Real-world Knowledge Injection

Yuwei Zhang, Wenhao Yu, Shangbin Feng, Yifan Zhu, Letian Peng, Jayanth Srinivasa, Gaowen Liu, Jingbo Shang

ACL 2026 Oral

WikiDYK benchmarks real-world knowledge injection from fresh Wikipedia facts and shows bidirectional language models memorize injected knowledge more reliably than causal LMs.

All publications