collaborators

6 papers

cs.CV2026

Role-Break in Attention Heads: Understanding and Detecting Hallucinations in VLMs

Mingyu Wang, Weilin Jin, Wenbo Li +5

Despite remarkable progress in vision-language generation, Vision-Language Models (VLMs) remain prone to hallucinations, producing content that is inconsistent with or unsupported…

cs.CV2026

HalluScope: Fine-grained Hallucination Diagnosis for Multimodal Large Language Models

Weilin Jin, Mingyu Wang, Wenbo Li +5

Although Multimodal Large Language Models have achieved strong performance across a wide range of vision-language tasks, they still suffer from hallucinations, where model outputs…

cs.CV2026

Geo3R: Mitigating Spatial Reasoning Hallucination in Multimodal Large Language Models

Mingyu Wang, Weilin Jin, Wenbo Li +3

Despite remarkable progress in visual understanding, Multimodal Large Language Models (MLLMs) remain prone to hallucinations when reasoning about spatial relationships, often produ…

cs.AI2026

StepFinder: A Temporal Semantic Framework for Failure Attribution in Multi-Agent Systems

Taiyu Zhu, Yifan Wu, Weilin Jin +2

LLM-based multi-agent systems exhibit remarkable collaborative capabilities in complex multi-step tasks. However, these systems are highly sensitive to single-step execution errors…

cs.SE2026

Can Language Models Go Beyond Coding? Assessing the Capability of Language Models to Build Real-World Systems

Chenyu Zhao, Shenglin Zhang, Zeshun Huang +8

Large language models (LLMs) have shown growing potential in software engineering, yet few benchmarks evaluate their ability to repair software during migration across instruction…

cs.SE2026

A Benchmark for Language Models in Real-World System Building

Weilin Jin, Chenyu Zhao, Zeshun Huang +12

During migration across instruction set architectures (ISAs), software package build repair is a critical task for ensuring the reliability of software deployment and the stability…