3 accepted papers
Face recognition remains vulnerable to presentation attacks, calling for robust Face Anti-Spoofing (FAS) solutions. Recent MLLM-based FAS methods reformulate the binary classification task as the generation of brief textual descriptions to improve cross-domain generalization. However, their generali
Recently, multimodal large language models (MLLMs) have achieved remarkable success in general multimodal tasks. Increasing attention has been given to leveraging MLLMs for fine-grained visual understanding, such as region-level captioning and pixel-level grounding. However, most existing approaches
MLLMs exhibit strong reasoning on isolated queries, yet they operate de novo--solving each problem independently and often repeating the same mistakes. Existing memory-augmented agents mainly store past trajectories for reuse. However, trajectory-based memory suffers from brevity bias, gradually los