Tag: Vision Foundation Model
All the articles with the tag "Vision Foundation Model".
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Task-Core Memory Management and Consolidation for Long-term Continual Learning
Published: at 11:01 AM
85.53 🤔This paper introduces Long-CL, a human memory-inspired framework for long-term continual learning, leveraging task-core memory management and selective sample consolidation to significantly outperform baselines by 7.4% and 6.5% AP on two novel benchmarks, MMLongCL-Bench and TextLongCL-Bench, while mitigating catastrophic forgetting.
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Unveiling the Compositional Ability Gap in Vision-Language Reasoning Model
Published: at 11:42 AM 85.21 🤔本文通过ComPABench基准评估视觉-语言模型（VLMs）的组合推理能力，发现强化学习（RL）优于监督微调（SFT）在跨任务和分布外泛化中的表现，并提出RL-Ground方法显著提升多模态组合推理性能。
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MMRL++: Parameter-Efficient and Interaction-Aware Representation Learning for Vision-Language Models
Published: at 11:16 AM 73.67 🤔本文提出MMRL及MMRL++框架，通过共享表示空间和解耦策略增强视觉-语言模型的少样本适配能力，并利用参数高效的SRRA和PRC机制提升泛化性和训练稳定性，在多个数据集上取得最优性能。
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VLM Q-Learning: Aligning Vision-Language Models for Interactive Decision-Making
Published: at 11:08 AM 70.12 🤔This paper introduces VLM Q-Learning, an offline-to-online reinforcement learning method that fine-tunes Vision-Language Models for interactive decision-making by filtering suboptimal actions with a critic head, achieving significant performance improvements over supervised fine-tuning across multiple multimodal agent tasks.
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How Do Multimodal Large Language Models Handle Complex Multimodal Reasoning? Placing Them in An Extensible Escape Game
Published: at 10:59 AM 68.75 🤔This paper introduces MM-Escape, a benchmark using the customizable 3D environment EscapeCraft to evaluate multimodal reasoning in MLLMs through room escape tasks, revealing that while models like GPT-4o achieve high success in simple scenarios, performance drops significantly with increased difficulty, exposing distinct limitations in reasoning and spatial awareness.