collaborators

5 papers

cs.CV2026

TMP: Tree-structured Mixed-policy Pruning for Large-scale Image Generation and Editing

Peizhen Zhang, Yang Li, Xunsong Li +10

Modern image generation model rapidly grows their sizes to meet high-fidelity image synthesis. However, they gradually become unaffordable for their enormous parameter consumption…

cs.DC2026

ASAP: A Disaggregated and Asynchronous Inference System for MoE Prefill

Weiwei Chen, Shuang Chen, Lele Li +5

Mixture-of-Experts (MoE) models have become the de facto standard for scaling large language models. To maintain computational efficiency, modern MoE serving systems typically empl…

cs.SE2025

VulnRepairEval: An Exploit-Based Evaluation Framework for Assessing Large Language Model Vulnerability Repair Capabilities

Weizhe Wang, Wei Ma, Qiang Hu +6

The adoption of Large Language Models (LLMs) for automated software vulnerability patching has shown promising outcomes on carefully curated evaluation sets. Nevertheless, existing…

cs.SE2025

Rethinking Testing for LLM Applications: Characteristics, Challenges, and a Lightweight Interaction Protocol

Wei Ma, Yixiao Yang, Qiang Hu +8

Applications of Large Language Models~(LLMs) have evolved from simple text generators into complex software systems that integrate retrieval augmentation, tool invocation, and mult…

cs.SE2025

Improving Code Understanding in Large Language Models through Concept-Aware Consistency Learning

Xiaoning Ren, Qiang Hu, Wei Ma +6

Large language models (LLMs) have recently shown impressive results on diverse code-related tasks, benefiting from large-scale training and instruction tuning. However, studies rev…