Researchers propose KBMR, the first MLLM-based embedding retriever for Knowledge-Based Visual Question Answering (KB-VQA), which outperforms CLIP baselines by up to 14.7% in retrieval Recall@1 and 9.4…
Researchers introduced Modality-Agnostic Refusal Steering (MARS), a method that uses text-based refusal strategies to enhance safety in multimodal language models without requiring unsafe multimodal d…
Researchers propose DocArena, a fully automated pipeline that transforms raw document collections into controllable training environments for document search agents, using multimodal large language mo…
Researchers have developed ICG, a framework that uses multimodal large language models and personalized preference alignment to generate cover images tailored to individual users. The system extracts …