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@HuggingPapers • 19,774 subscribers

Tweeting interesting papers submitted at https://t.co/rXX8x0HzXV. Submit your own at https://t.co/QhbJKXBd4Q, and link models/datasets/demos to it!

Shorts

ByteDance Seed is back with SeedVR2, now on Hugging Face! This one-step video restoration model leverages diffusion adversarial post-training for impressive results, even on high-resolution videos.

ByteDance Seed is back with SeedVR2, now on Hugging Face! This one-step video restoration model leverages diffusion adversarial post-training for impressive results, even on high-resolution videos.

54,539 просмотров

Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model? New paper questions the common assumption that RLVR helps LLMs acquire novel reasoning abilities.

Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model? New paper questions the common assumption that RLVR helps LLMs acquire novel reasoning abilities.

52,092 просмотров

Unlock precise 3D object editing with NANO3D! This training-free framework offers coherent, mask-free edits for game, animation, and robotics content. It even preserves unedited regions perfectly.

Unlock precise 3D object editing with NANO3D! This training-free framework offers coherent, mask-free edits for game, animation, and robotics content. It even preserves unedited regions perfectly.

11,800 просмотров

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NVIDIA just released AnyFlow on Hugging Face The first any-step video diffusion model that generates high-quality text-to-video with any inference budget - 4 steps or 50, quality scales smoothly without degradation.

NVIDIA just released AnyFlow on Hugging Face The first any-step video diffusion model that generates high-quality text-to-video with any inference budget - 4 steps or 50, quality scales smoothly without degradation.

41,670 просмотров • 2 месяцев назад

Microsoft Research introduces Mirage Latent spatial memory stores 3D scenes directly as latent tokens, skipping the costly RGB render-and-reencode loop. The result is up to 10.57x faster video generation, 55x lower memory use, and state-of-the-art consistency on WorldScore.

Microsoft Research introduces Mirage Latent spatial memory stores 3D scenes directly as latent tokens, skipping the costly RGB render-and-reencode loop. The result is up to 10.57x faster video generation, 55x lower memory use, and state-of-the-art consistency on WorldScore.

18,691 просмотров • 1 месяц назад

Introducing the Daily Papers SKILL.md Enables agents to > read paper content as markdown > search papers > find linked Hugging Face models and datasets > fetch the papers API > and more! Link below ⬇️

Introducing the Daily Papers SKILL.md Enables agents to > read paper content as markdown > search papers > find linked Hugging Face models and datasets > fetch the papers API > and more! Link below ⬇️

34,076 просмотров • 4 месяцев назад

MinerU-Diffusion A 2.5B diffusion-based OCR model that replaces slow autoregressive decoding with parallel block-wise diffusion, achieving up to 3.2x faster inference while improving robustness on complex documents with tables, formulas, and layouts.

MinerU-Diffusion A 2.5B diffusion-based OCR model that replaces slow autoregressive decoding with parallel block-wise diffusion, achieving up to 3.2x faster inference while improving robustness on complex documents with tables, formulas, and layouts.

15,304 просмотров • 3 месяцев назад

DynamicVLA A compact 0.4B Vision-Language-Action model that finally lets robots manipulate *moving* objects in real-time, closing the perception-execution gap with Continuous Inference and Latent-aware Action Streaming.

DynamicVLA A compact 0.4B Vision-Language-Action model that finally lets robots manipulate moving objects in real-time, closing the perception-execution gap with Continuous Inference and Latent-aware Action Streaming.

16,357 просмотров • 5 месяцев назад

Microsoft just dropped VITRA-VLA, a new Vision-Language-Action model for robotics on Hugging Face. It learns dexterous manipulation from over 1 million real-life human hand activity videos.

Microsoft just dropped VITRA-VLA, a new Vision-Language-Action model for robotics on Hugging Face. It learns dexterous manipulation from over 1 million real-life human hand activity videos.

19,177 просмотров • 7 месяцев назад

Zhipu AI just released GLM-4.6V on Hugging Face This new multimodal model achieves SOTA visual understanding, features native function calling for agents, and handles 128k context for documents. Perception to action!

Zhipu AI just released GLM-4.6V on Hugging Face This new multimodal model achieves SOTA visual understanding, features native function calling for agents, and handles 128k context for documents. Perception to action!

16,629 просмотров • 7 месяцев назад

Self-Forcing++ for minute-scale video generation ByteDance's new method generates high-quality videos up to 4 min 15 sec! It scales diffusion models without long-video teachers or retraining, preserving fidelity and consistency.

Self-Forcing++ for minute-scale video generation ByteDance's new method generates high-quality videos up to 4 min 15 sec! It scales diffusion models without long-video teachers or retraining, preserving fidelity and consistency.

17,720 просмотров • 9 месяцев назад

Tencent ARC Lab releases FlexiAct on Hugging Face Transfers actions from a reference video to an arbitrary target image! Allows for variations in layout, viewpoint, and skeletal structure

Tencent ARC Lab releases FlexiAct on Hugging Face Transfers actions from a reference video to an arbitrary target image! Allows for variations in layout, viewpoint, and skeletal structure

10,792 просмотров • 1 год назад

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