5 papers
SP-Mamba: Spatial-Perception State Space Model for Unsupervised Medical Anomaly Detection
Rui Pan, Ruiying Lu
Radiography imaging protocols target on specific anatomical regions, resulting in highly consistent images with recurrent structural patterns across patients. Recent advances in me…
MINT: Memory-Infused Prompt Tuning at Test-time for CLIP
Jiaming Yi, Ruirui Pan, Jishen Yang +1
Improving the generalization ability of Vision-Language Pre-trained Models (VLMs) under test-time data distribution shifts remains a critical challenge. The existing Test-Time Adap…
Safe RLHF-V: Safe Reinforcement Learning from Multi-modal Human Feedback
Jiaming Ji, Xinyu Chen, Rui Pan +13
Multimodal large language models (MLLMs) are essential for building general-purpose AI assistants; however, they pose increasing safety risks. How can we ensure safety alignment of…
Align Anything: Training All-Modality Models to Follow Instructions with Language Feedback
Jiaming Ji, Jiayi Zhou, Hantao Lou +16
Reinforcement learning from human feedback (RLHF) has proven effective in enhancing the instruction-following capabilities of large language models; however, it remains underexplor…
CollaMamba: Efficient Collaborative Perception with Cross-Agent Spatial-Temporal State Space Model
Yang Li, Quan Yuan, Guiyang Luo +5
By sharing complementary perceptual information, multi-agent collaborative perception fosters a deeper understanding of the environment. Recent studies on collaborative perception…