DeepSeekHugging Face · DeepSeek 새 모델
deepseek-ai/DeepSeek-V4.1-Flash-1017
image-text-to-text · transformers
#멀티모달
13건 · 최신순
Hugging FaceHugging Face 일일 논문
FlashMask-3: Efficient and Expressive Mask-Aware Distributed Attention
Long-context training of large language and multimodal models couples structured attention masks (document, prefix-LM, share-question, sliding-window, block-sparse) with multi-node context parallelism, making the mask a dominant bottleneck.
Hugging FaceHugging Face 일일 논문
MMSearch-OPD: Easy Made Hard, Hard Made Learnable for Long-Horizon Multimodal Search Agents
Multimodal deep search is moving from short queries to long-horizon investigations that continually acquire evidence.
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RoTA-Bench: Evaluating 3D Spatial Reasoning through Interactive Projection Alignment
Can vision-language models turn 2D observations into 3D understanding that supports precise action? This requires inferring object geometry, anticipating the effects of rotation, and refining actions through visual feedback.
Hugging FaceHugging Face 일일 논문
CarryOn: A Dual-Loop Harness for Personalized and Reliable Robot Assistance
While generalist vision-language-action (VLA) models have enabled diverse open-world manipulation, real-world robotic assistance requires two critical capabilities they currently lack: personalization and reliable execution.
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PAIR: Bridging Perception and Action in Vision-Language-Action Models
Vision-language-action (VLA) models map visual observations and language instructions to continuous robot actions.
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OmniVerifier-C1: Decomposed Graded Verifier for Rule-Governed Generative World Modeling
Generative visual verifiers play a crucial role in advancing multimodal intelligence. To enhance the robustness of visual verifiers in complex multimodal scenarios involving compositional requirements, we move beyond conventional binary…
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WorldCast: Exploring Intelligent Visual Generation in World State Prediction
Humans interpret multimodal observations of the world and forecast how it will evolve. Recent multimodal generative systems have demonstrated similar capabilities: they can integrate multimodal context and synthesize visual outputs that…
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MJev-Spatial: System One Spatial Intelligence via Native Attention Matching
Spatial intelligence lets an agent perceive and act in the physical world, and many of its judgments must be made at interaction rates: which spatial relation holds, how far an object is, or where to place it.
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Equal CER, Unequal Damage: Severity-Weighted Character Error Rate for OCR
Character Error Rate (CER), the standard metric for OCR and vision-language models (VLMs), charges a typo as much as a wrong name.
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VLA-Δ: Learning Physical State Transition for Vision-Language-Action Models
Vision-language-action (VLA) models transfer semantic knowledge acquired through vision-language pretraining to robot control, achieving strong performance across various benchmarks.
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PINT: A Unified Model with Shared Predictive Intent for Robot Manipulation
Generalist robot manipulation can benefit from pretrained vision-language models (VLMs) for semantic reasoning and video generation models (VGMs) for world modeling.
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CoWorld Reasoner: Agentic Multimodal Reasoning with the Evolving Video World Model-Driven Harness
As Vision-Language Models (VLMs) advance, they are increasingly expected to perform spatiotemporal reasoning over motion, actions, and view changes beyond what the input images show.