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cs.CV2026
Chain of Modality: From Static Fusion to Dynamic Orchestration in Omni-MLLMs
Ziyang Luo, Nian Liu, Junwei Han
Omni-modal Large Language Models (Omni-MLLMs) promise a unified integration of diverse sensory streams. However, recent evaluations reveal a critical performance paradox: unimodal…
cs.CV2025
Saliency-R1: Incentivizing Unified Saliency Reasoning Capability in MLLM with Confidence-Guided Reinforcement Learning
Long Li, Shuichen Ji, Ziyang Luo +4
Although multimodal large language models (MLLMs) excel in high-level vision-language reasoning, they lack inherent awareness of visual saliency, making it difficult to identify ke…
cs.CV2024
Unsupervised Pre-training with Language-Vision Prompts for Low-Data Instance Segmentation
Dingwen Zhang, Hao Li, Diqi He +4
In recent times, following the paradigm of DETR (DEtection TRansformer), query-based end-to-end instance segmentation (QEIS) methods have exhibited superior performance compared to…