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.

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.
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.

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.
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.

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.
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.