collaborators

6 papers

cs.CR2025

SafePTR: Token-Level Jailbreak Defense in Multimodal LLMs via Prune-then-Restore Mechanism

Beitao Chen, Xinyu Lyu, Lianli Gao +2

By incorporating visual inputs, Multimodal Large Language Models (MLLMs) extend LLMs to support visual reasoning. However, this integration also introduces new vulnerabilities, mak…

cs.CV2025

FlexAC: Towards Flexible Control of Associative Reasoning in Multimodal Large Language Models

Shengming Yuan, Xinyu Lyu, Shuailong Wang +3

Multimodal large language models (MLLMs) face an inherent trade-off between faithfulness and creativity, as different tasks require varying degrees of associative reasoning. Howeve…

cs.CV2025

Alleviating Hallucinations in Large Vision-Language Models through Hallucination-Induced Optimization

Xinyu Lyu, Beitao Chen, Lianli Gao +2

Although Large Visual Language Models (LVLMs) have demonstrated exceptional abilities in understanding multimodal data, they invariably suffer from hallucinations, leading to a dis…

cs.CV2025

Attention Hijackers: Detect and Disentangle Attention Hijacking in LVLMs for Hallucination Mitigation

Beitao Chen, Xinyu Lyu, Lianli Gao +2

Despite their success, Large Vision-Language Models (LVLMs) remain vulnerable to hallucinations. While existing studies attribute the cause of hallucinations to insufficient visual…

cs.CV2024

ALF: Adaptive Label Finetuning for Scene Graph Generation

Qishen Chen, Jianzhi Liu, Xinyu Lyu +3

Scene Graph Generation (SGG) endeavors to predict the relationships between subjects and objects in a given image. Nevertheless, the long-tail distribution of relations often leads…

cs.CV2024

Informative Scene Graph Generation via Debiasing

Lianli Gao, Xinyu Lyu, Yuyu Guo +5

Scene graph generation aims to detect visual relationship triplets, (subject, predicate, object). Due to biases in data, current models tend to predict common predicates, e.g. "on"…