4 papers
Better, Stronger, Faster, and Broader: Structured All-Mask Prediction for MLLM-Based Segmentation
Jiazhen Liu, Mingkuan Feng, Long Chen
MLLM-based segmentation faces a core segmentation trilemma: high segmentation performance, preserved dialogue ability, and fast inference. Embedding-prediction methods may disrupt…
Empowering Small VLMs to Think with Dynamic Memorization and Exploration
Jiazhen Liu, Yuchuan Deng, Long Chen
Small-scale Vision-Language Models (SVLMs) are exceptionally well-suited for proprietary tasks. Equipping them with thinking capabilities is a critical step to enhance their perfor…
Better, Stronger, Faster: Tackling the Trilemma in MLLM-based Segmentation with Simultaneous Textual Mask Prediction
Jiazhen Liu, Mingkuan Feng, Long Chen
Integrating segmentation into Multimodal Large Language Models (MLLMs) presents a core trilemma: simultaneously preserving dialogue ability, achieving high segmentation performance…
Segmentation as A Plug-and-Play Capability for Frozen Multimodal LLMs
Jiazhen Liu, Long Chen
Integrating diverse visual capabilities into a unified model is a significant trend in Multimodal Large Language Models (MLLMs). Among these, the inclusion of segmentation poses a…