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https://arxiv.org/pdf/2411.07133

https://arxiv.org/pdf/2411.04997

https://arxiv.org/pdf/2410.02080

https://arxiv.org/pdf/2411.07232

https://arxiv.org/pdf/2411.08147Large language models (LLMs) have achieved substantial progress in processing long contexts but still struggle with long-context reasoning. Existing approaches typically involve fine-tuning LLMs with synthetic data, which depends on annotations from human experts or advanced models like GPT-4, thus restricting further advancements. To address this issue, we invest..

https://arxiv.org/abs/2405.17430

https://arxiv.org/pdf/2407.02392

https://arxiv.org/pdf/2411.04109

https://arxiv.org/pdf/2411.03312https://github.com/locuslab/llava-token-compression.Let me format the text with line breaks for each sentence: Vision Language Models (VLMs) have demonstrated strong capabilities across various visual understanding and reasoning tasks. However, their real-world deployment is often constrained by high latency during inference due to substantial compute required to ..

https://arxiv.org/pdf/2411.02359 https://github.com/yueyang130/DeeR-VLA.Let me help you format each sentence with line breaks: Multimodal Large Language Models (MLLMs) have demonstrated remarkable comprehension and reasoning capabilities with complex language and visual data. These advances have spurred the vision of establishing a generalist robotic MLLM proficient in understanding complex huma..