1 citations · 1 across the 11 of their papers we have counts for
12 papers
CSPO: Alleviating Reward Ambiguity for Structured Table-to-LaTeX Generation
Yunfan Yang, Cuiling Lan, Jitao Sang +1
Tables contain rich structured information, yet when stored as images their contents remain "locked" within pixels. Converting table images into LaTeX code enables faithful digitiz…
HulluEdit: Single-Pass Evidence-Consistent Subspace Editing for Mitigating Hallucinations in Large Vision-Language Models
Yangguang Lin, Quan Fang, Yufei Li +3
Object hallucination in Large Vision-Language Models (LVLMs) significantly hinders their reliable deployment. Existing methods struggle to balance efficiency and accuracy: they oft…
GUITester: Enabling GUI Agents for Exploratory Defect Discovery
Yifei Gao, Jiang Wu, Xiaoyi Chen +5
Exploratory GUI testing is essential for software quality but suffers from high manual costs. While Multi-modal Large Language Model (MLLM) agents excel in navigation, they fail to…
WebSynthesis: World-Model-Guided MCTS for Efficient WebUI-Trajectory Synthesis
Yifei Gao, Junhong Ye, Jiaqi Wang +1
Recent advancements in large language models (LLMs) have significantly improved the capabilities of web agents. However, effectively navigating complex and dynamic web environments…
NAP-Tuning: Neural Augmented Prompt Tuning for Adversarially Robust Vision-Language Models
Jiaming Zhang, Xin Wang, Xingjun Ma +3
Vision-Language Models (VLMs) such as CLIP have demonstrated remarkable capabilities in understanding relationships between visual and textual data through joint embedding spaces.…
Mind with Eyes: from Language Reasoning to Multimodal Reasoning
Zhiyu Lin, Yifei Gao, Xian Zhao +2
Language models have recently advanced into the realm of reasoning, yet it is through multimodal reasoning that we can fully unlock the potential to achieve more comprehensive, hum…
Debiased Prompt Tuning in Vision-Language Model without Annotations
Chaoquan Jiang, Yunfan Yang, Rui Hu +1
Prompt tuning of Vision-Language Models (VLMs) such as CLIP, has demonstrated the ability to rapidly adapt to various downstream tasks. However, recent studies indicate that tuned…
Agent models: Internalizing Chain-of-Action Generation into Reasoning models
Yuxiang Zhang, Yuqi Yang, Jiangming Shu +2
Traditional agentic workflows rely on external prompts to manage interactions with tools and the environment, which limits the autonomy of reasoning models. We position \emph{Large…
VaLiD: Mitigating the Hallucination of Large Vision Language Models by Visual Layer Fusion Contrastive Decoding
Jiaqi Wang, Yifei Gao, Jitao Sang
Large Vision-Language Models (LVLMs) have demonstrated remarkable capabilities in multimodal task reasoning. However, they often generate responses that appear plausible yet do not…
Debiasing Vison-Language Models with Text-Only Training
Yunfan Yang, Chaoquan Jiang, Zhiyu Lin +3
Pre-trained vision-language models (VLMs), such as CLIP, have exhibited remarkable performance across various downstream tasks by aligning text and images in a unified embedding sp…
AnyAttack: Towards Large-scale Self-supervised Adversarial Attacks on Vision-language Models
Jiaming Zhang, Junhong Ye, Xingjun Ma +5
Due to their multimodal capabilities, Vision-Language Models (VLMs) have found numerous impactful applications in real-world scenarios. However, recent studies have revealed that V…
AIGCs Confuse AI Too: Investigating and Explaining Synthetic Image-induced Hallucinations in Large Vision-Language Models
Yifei Gao, Jiaqi Wang, Zhiyu Lin +1
The evolution of Artificial Intelligence Generated Contents (AIGCs) is advancing towards higher quality. The growing interactions with AIGCs present a new challenge to the data-dri…