Chongyang Tao

Patient–trial retrieval is a challenging problem that requires nuanced clinical reasoning beyond surface-level semantic similarity. However, scarce and costly relevance annotations force existing approaches to rely on very limited supervision or zero-shot transfer, reducing the task to generic se...

Diffusion Large Language Models (dLLMs) have recently become a promising alternative to autoregressive large language models (ARMs). Semi-autoregressive (Semi-AR) decoding is widely employed in base dLLMs and advanced decoding strategies due to its superior performance. However, our observations...

Large language models (LLMs) substantially enhance developer productivity in repository-level code generation through interactive collaboration. However, as interactions progress, repository context must be continuously preserved and updated to integrate newly validated information. Meanwhile, th...