5 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…
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…
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…
ClothPPO: A Proximal Policy Optimization Enhancing Framework for Robotic Cloth Manipulation with Observation-Aligned Action Spaces
Libing Yang, Yang Li, Long Chen
Vision-based robotic cloth unfolding has made great progress recently. However, prior works predominantly rely on value learning and have not fully explored policy-based techniques…