FlowSeg: Dynamic Semantic Guidance for LLM-Conditioned Segmentation 事件

FlowSeg: Dynamic Semantic Guidance for LLM-Conditioned Segmentation arXiv:2605.29461v1 Announce Type: new Abstract: LLM-conditioned segmentation has recently advanced rapidly by coupling large language models with iterative mask generation frameworks. However, we identify a persistent failure mode in current propose-then-select pipelines. Although high-quality mask candidates are often generated, the final prediction may fail to match the given linguistic condition. This failure arises because