11 papers
Rethinking Attention Locality in Spiking Transformers
Zeqi Zheng, Zizheng Zhu, Yuping Yan +3
Spiking Transformers provide a promising paradigm for efficient visual processing with spike-driven computation, yet their Softmax-free Spiking Self-Attention (SSA) struggles to es…
HMACE: Heterogeneous Multi-Agent Collaborative Evolution for Combinatorial Optimization
Yuping Yan, Jirui Han, Fei Ming +2
Large Language Models have recently emerged as a promising paradigm for automated heuristic design for NP-hard combinatorial optimization problems. Despite this progress, existing…
STRONG-VLA: Decoupled Robustness Learning for Vision-Language-Action Models under Multimodal Perturbations
Yuhan Xie, Yuping Yan, Yunqi Zhao +2
Despite their strong performance in embodied tasks, recent Vision-Language-Action (VLA) models remain highly fragile under multimodal perturbations, where visual corruption and lin…
OutSafe-Bench: A Benchmark for Multimodal Offensive Content Detection in Large Language Models
Yuping Yan, Yuhan Xie, Yuanshuai Li +3
Since Multimodal Large Language Models (MLLMs) are increasingly being integrated into everyday tools and intelligent agents, growing concerns have arisen regarding their possible o…
IRIS: Implicit Reward-Guided Internal Sifting for Mitigating Multimodal Hallucination
Yuanshuai Li, Yuping Yan, Jirui Han +3
Hallucination remains a fundamental challenge for Multimodal Large Language Models (MLLMs). While Direct Preference Optimization (DPO) is a key alignment framework, existing approa…
Adversarial Robustness in Zero-Shot Learning:An Empirical Study on Class and Concept-Level Vulnerabilities
Zhiyuan Peng, Zihan Ye, Shreyank N Gowda +3
Zero-shot Learning (ZSL) aims to enable image classifiers to recognize images from unseen classes that were not included during training. Unlike traditional supervised classificati…