1 citations · 2 across the 23 of their papers we have counts for
8 papers · 1 filter
From Pixel to Coding: Evaluating the Figure Reproduction Capabilities of MLLMs
Zijian Chen, Zhengyu Chen, Bohan Liang +7
Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in both visual understanding and code generation. However, existing benchmarks typically evaluate…
SafeAtlas-VL: Beyond Binary Multimodal Safety with Large-Scale Data and Guard Models
Zongrui Wang, Xiangyang Zhu, Sicheng Wang +13
Multimodal safety moderation requires distinguishing risks arising from visual content, user intent, and assistant behavior. Existing safeguards, however, are typically trained for…
Emergent Misalignment Can Be Induced by Sycophancy and Reversed via Alignment Gating
Sicheng Wang, Xiangyang Zhu, Han Wang +6
Prior work has shown that fine-tuning large language models on malicious or incorrect outputs in narrow domains can induce broad misalignment and harmful behavior, a phenomenon kno…
NTIRE 2026 The 3rd Restore Any Image Model (RAIM) Challenge: Professional Image Quality Assessment (Track 1)
Guanyi Qin, Jie Liang, Bingbing Zhang +50
In this paper, we present an overview of the NTIRE 2026 challenge on the 3rd Restore Any Image Model in the Wild, specifically focusing on Track 1: Professional Image Quality Asses…
SafeSci: Safety Evaluation of Large Language Models in Science Domains and Beyond
Xiangyang Zhu, Yuan Tian, Qi Jia +14
The success of large language models (LLMs) in scientific domains has heightened safety concerns, prompting numerous benchmarks to evaluate their scientific safety. Existing benchm…
LifeEval: A Multimodal Benchmark for Assistive AI in Egocentric Daily Life Tasks
Hengjian Gao, Kaiwei Zhang, Shibo Wang +8
The rapid progress of Multimodal Large Language Models (MLLMs) marks a significant step toward artificial general intelligence, offering great potential for augmenting human capabi…
QualiRAG: Retrieval-Augmented Generation for Visual Quality Understanding
Linhan Cao, Wei Sun, Weixia Zhang +6
Visual quality assessment (VQA) is increasingly shifting from scalar score prediction toward interpretable quality understanding -- a paradigm that demands \textit{fine-grained spa…
KidVis: Do Multimodal Large Language Models Possess the Visual Perceptual Capabilities of a 6-Year-Old?
Xianfeng Wang, Kaiwei Zhang, Qi Jia +3
While Multimodal Large Language Models (MLLMs) have demonstrated impressive proficiency in high-level reasoning tasks, such as complex diagrammatic interpretation, it remains an op…