1 citations · 2 across the 20 of their papers we have counts for
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QuadSentinel: Sequent Safety for Machine-Checkable Control in Multi-agent Systems
Yiliu Yang, Yilei Jiang, Qunzhong Wang +5
Safety risks arise as large language model-based agents solve complex tasks with tools, multi-step plans, and inter-agent messages. However, deployer-written policies in natural la…
OneThinker: All-in-one Reasoning Model for Image and Video
Kaituo Feng, Manyuan Zhang, Hongyu Li +11
Reinforcement learning (RL) has recently achieved remarkable success in eliciting visual reasoning within Multimodal Large Language Models (MLLMs). However, existing approaches typ…
ConceptGuard: Proactive Safety in Text-and-Image-to-Video Generation through Multimodal Risk Detection
Ruize Ma, Minghong Cai, Yilei Jiang +7
Recent progress in video generative models has enabled the creation of high-quality videos from multimodal prompts that combine text and images. While these systems offer enhanced…
VR-Thinker: Boosting Video Reward Models through Thinking-with-Image Reasoning
Qunzhong Wang, Jie Liu, Jiajun Liang +7
Recent advancements in multimodal reward models (RMs) have substantially improved post-training for visual generative models. However, current RMs face inherent limitations: (1) vi…
ScreenCoder: Advancing Visual-to-Code Generation for Front-End Automation via Modular Multimodal Agents
Yilei Jiang, Yaozhi Zheng, Yuxuan Wan +4
Automating the transformation of user interface (UI) designs into front-end code holds significant promise for accelerating software development and democratizing design workflows.…
MSR-Align: Policy-Grounded Multimodal Alignment for Safety-Aware Reasoning in Vision-Language Models
Yinan Xia, Yilei Jiang, Yingshui Tan +3
Vision-Language Models (VLMs) have achieved remarkable progress in multimodal reasoning tasks through enhanced chain-of-thought capabilities. However, this advancement also introdu…
MME-Reasoning: A Comprehensive Benchmark for Logical Reasoning in MLLMs
Jiakang Yuan, Tianshuo Peng, Yilei Jiang +8
Logical reasoning is a fundamental aspect of human intelligence and an essential capability for multimodal large language models (MLLMs). Despite the significant advancement in mul…
Equilibrate RLHF: Towards Balancing Helpfulness-Safety Trade-off in Large Language Models
Yingshui Tan, Yilei Jiang, Yanshi Li +6
Fine-tuning large language models (LLMs) based on human preferences, commonly achieved through reinforcement learning from human feedback (RLHF), has been effective in improving th…
HiddenDetect: Detecting Jailbreak Attacks against Large Vision-Language Models via Monitoring Hidden States
Yilei Jiang, Xinyan Gao, Tianshuo Peng +4
The integration of additional modalities increases the susceptibility of large vision-language models (LVLMs) to safety risks, such as jailbreak attacks, compared to their language…