✨Wan-Move: Motion-controllable Video Generation via Latent Trajectory Guidance

📝 Summary:
Wan-Move brings precise, scalable motion control to video generation. It projects object trajectories into latent space, creating motion-aware features to guide existing models without architectural changes. This yields high-quality 480p videos with motion control rivaling commercial tools.

🔹 Publication Date: Published on Dec 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.08765
• PDF: https://arxiv.org/pdf/2512.08765
• Github: https://wan-move.github.io/

🔹 Models citing this paper:
• https://huggingface.co/Ruihang/Wan-Move-14B-480P

✨ Datasets citing this paper:
• https://huggingface.co/datasets/Ruihang/MoveBench

==================================

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✨TrackingWorld: World-centric Monocular 3D Tracking of Almost All Pixels

📝 Summary:
TrackingWorld provides dense 3D tracking of pixels in a world-centric coordinate system by upsampling sparse 2D tracks and optimizing camera poses and 3D coordinates. AI-generated summary Monocular 3D...

🔹 Publication Date: Published on Dec 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.08358
• PDF: https://arxiv.org/pdf/2512.08358
• Project Page: https://igl-hkust.github.io/TrackingWorld.github.io/

==================================

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨TreeGRPO: Tree-Advantage GRPO for Online RL Post-Training of Diffusion Models

📝 Summary:
TreeGRPO, a novel RL framework, enhances training efficiency for generative models by using a tree-structured denoising process, leading to faster training and better performance. AI-generated summary...

🔹 Publication Date: Published on Dec 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.08153
• PDF: https://arxiv.org/pdf/2512.08153

==================================

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✨Preserving Source Video Realism: High-Fidelity Face Swapping for Cinematic Quality

📝 Summary:
LivingSwap enhances video face swapping by using keyframes and reference guidance to maintain identity and fidelity over long sequences, reducing manual effort and achieving state-of-the-art results. ...

🔹 Publication Date: Published on Dec 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.07951
• PDF: https://arxiv.org/pdf/2512.07951
• Project Page: https://aim-uofa.github.io/LivingSwap

==================================

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✨EcomBench: Towards Holistic Evaluation of Foundation Agents in E-commerce

📝 Summary:
EcomBench is a benchmark that evaluates agent performance in real-world e-commerce environments through deep information retrieval, multi-step reasoning, and cross-source knowledge integration. AI-gen...

🔹 Publication Date: Published on Dec 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.08868
• PDF: https://arxiv.org/pdf/2512.08868

==================================

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✨DeepCode: Open Agentic Coding

📝 Summary:
DeepCode, a fully autonomous framework, addresses the challenges of document-to-codebase synthesis by optimizing information flow through source compression, structured indexing, knowledge injection, ...

🔹 Publication Date: Published on Dec 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.07921
• PDF: https://arxiv.org/pdf/2512.07921
• Github: https://github.com/HKUDS/DeepCode

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✨ThreadWeaver: Adaptive Threading for Efficient Parallel Reasoning in Language Models

📝 Summary:
ThreadWeaver, a framework for adaptive parallel reasoning, achieves accuracy comparable to sequential models while reducing inference latency through parallel trajectory generation, trie-based trainin...

🔹 Publication Date: Published on Nov 24

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.07843
• PDF: https://arxiv.org/pdf/2512.07843

==================================

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✨Modular Neural Image Signal Processing

📝 Summary:
A modular neural ISP framework provides high rendering accuracy, scalability, and flexibility for diverse photo-editing operations with competitive results. AI-generated summary This paper presents a ...

🔹 Publication Date: Published on Dec 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.08564
• PDF: https://arxiv.org/pdf/2512.08564

==================================

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✨Ground Slow, Move Fast: A Dual-System Foundation Model for Generalizable Vision-and-Language Navigation

📝 Summary:
DualVLN is a dual-system model for vision-language navigation. It integrates a VLM global planner with a fast local policy for smooth actions, enabling robust real-time control and long-horizon planning in dynamic environments.

🔹 Publication Date: Published on Dec 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.08186
• PDF: https://arxiv.org/pdf/2512.08186
• Project Page: https://internrobotics.github.io/internvla-n1-dualvln.github.io/
• Github: https://github.com/InternRobotics/InternNav

🔹 Models citing this paper:
• https://huggingface.co/InternRobotics/InternVLA-N1-System2
• https://huggingface.co/InternRobotics/InternVLA-N1-w-NavDP
• https://huggingface.co/InternRobotics/InternVLA-N1-DualVLN

==================================

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✨From Next-Token to Next-Block: A Principled Adaptation Path for Diffusion LLMs

📝 Summary:
This paper introduces a principled method to adapt autoregressive LLMs into block-wise diffusion models, enabling efficient parallel generation. This adaptation retains pretrained knowledge, achieving state-of-the-art performance for 7B diffusion LLMs, and avoids expensive training from scratch.

🔹 Publication Date: Published on Dec 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.06776
• PDF: https://arxiv.org/pdf/2512.06776

==================================

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#LLM #DiffusionModels #AI #ParallelGeneration #MachineLearning

✨Same Content, Different Answers: Cross-Modal Inconsistency in MLLMs

📝 Summary:
New benchmarks reveal MLLMs struggle with cross-modal inconsistency, failing to reason consistently across image, text, and mixed modalities with the same information. Visual characteristics like color and resolution significantly impact performance, even when text recognition is perfect. This hi...

🔹 Publication Date: Published on Dec 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.08923
• PDF: https://arxiv.org/pdf/2512.08923

==================================

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#MLLMs #CrossModalAI #AIResearch #ComputerVision #NLP

✨Predicting Time-Dependent Flow Over Complex Geometries Using Operator Networks

📝 Summary:
A Deep Operator Network predicts unsteady flow velocity fields over complex geometries with up to 1000X speedup over traditional simulations. It accurately captures near-term transients but shows error accumulation in fine-scale wakes.

🔹 Publication Date: Published on Dec 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.04434
• PDF: https://arxiv.org/pdf/2512.04434
• Github: https://github.com/baskargroup/TimeDependent-DeepONet

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#DeepLearning #FluidDynamics #AI #CFD #MachineLearning

✨MIND-V: Hierarchical Video Generation for Long-Horizon Robotic Manipulation with RL-based Physical Alignment

📝 Summary:
MIND-V generates long-horizon, physically plausible robotic manipulation videos. This hierarchical framework uses semantic reasoning and an RL-based physical alignment strategy to synthesize robust, coherent actions, addressing data scarcity.

🔹 Publication Date: Published on Dec 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.06628
• PDF: https://arxiv.org/pdf/2512.06628
• Project Page: https://github.com/Richard-Zhang-AI/MIND-V
• Github: https://github.com/Richard-Zhang-AI/MIND-V

==================================

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#Robotics #VideoGeneration #ReinforcementLearning #AI #MachineLearning

✨OneStory: Coherent Multi-Shot Video Generation with Adaptive Memory

📝 Summary:
OneStory generates coherent multi-shot videos by modeling global cross-shot context. It uses a Frame Selection module and an Adaptive Conditioner for next-shot generation, leveraging pretrained models and a new dataset. This achieves state-of-the-art narrative coherence for long-form video storyt...

🔹 Publication Date: Published on Dec 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.07802
• PDF: https://arxiv.org/pdf/2512.07802
• Project Page: https://zhaochongan.github.io/projects/OneStory/

==================================

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#VideoGeneration #AI #DeepLearning #ComputerVision #GenerativeAI

✨LYNX: Learning Dynamic Exits for Confidence-Controlled Reasoning

📝 Summary:
LYNX is an early-exit mechanism for large reasoning models that prevents overthinking. It uses hidden-state awareness and reasoning cues for confidence-controlled stopping, significantly reducing tokens by 40-70% while maintaining or improving accuracy across diverse tasks with a single trained p...

🔹 Publication Date: Published on Dec 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.05325
• PDF: https://arxiv.org/pdf/2512.05325
• Github: https://github.com/farukakgul/LYNX

🔹 Models citing this paper:
• https://huggingface.co/farukakgul/LYNX

==================================

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#LLM #AI #MachineLearning #EarlyExit #Efficiency

✨Visionary: The World Model Carrier Built on WebGPU-Powered Gaussian Splatting Platform

📝 Summary:
Visionary is a web-native platform for real-time 3D Gaussian Splatting and mesh rendering. It uses WebGPU and per-frame ONNX inference for dynamic content and generative models, offering efficient, browser-based deployment and support for various neural rendering methods.

🔹 Publication Date: Published on Dec 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.08478
• PDF: https://arxiv.org/pdf/2512.08478
• Project Page: https://visionary-laboratory.github.io/visionary/
• Github: https://visionary-laboratory.github.io/visionary/

==================================

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#GaussianSplatting #WebGPU #NeuralRendering #3DGraphics #GenerativeAI

✨SUCCESS-GS: Survey of Compactness and Compression for Efficient Static and Dynamic Gaussian Splatting

📝 Summary:
This survey overviews efficient 3D and 4D Gaussian Splatting. It categorizes parameter and restructuring compression methods to reduce memory and computation while maintaining reconstruction quality. It also covers current limitations and future research.

🔹 Publication Date: Published on Dec 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.07197
• PDF: https://arxiv.org/pdf/2512.07197
• Project Page: https://cmlab-korea.github.io/Awesome-Efficient-GS/
• Github: https://cmlab-korea.github.io/Awesome-Efficient-GS/

==================================

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#GaussianSplatting #3DVision #ComputerGraphics #DeepLearning #Efficiency

✨Boosting Unsupervised Video Instance Segmentation with Automatic Quality-Guided Self-Training

📝 Summary:
AutoQ-VIS is an unsupervised Video Instance Segmentation framework that bridges the synthetic-to-real domain gap. It uses quality-guided self-training with automatic quality assessment for progressive adaptation. This method achieves state-of-the-art results without requiring human annotations.

🔹 Publication Date: Published on Dec 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.06864
• PDF: https://arxiv.org/pdf/2512.06864
• Github: https://github.com/wcbup/AutoQ-VIS/

==================================

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#VideoInstanceSegmentation #UnsupervisedLearning #ComputerVision #MachineLearning #DeepLearning

✨Efficiently Reconstructing Dynamic Scenes One D4RT at a Time

📝 Summary:
D4RT is a transformer-based model that efficiently reconstructs 4D scenes from videos. It uses a novel querying mechanism to infer depth and motion by flexibly probing 3D space-time points, outperforming previous methods.

🔹 Publication Date: Published on Dec 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.08924
• PDF: https://arxiv.org/pdf/2512.08924

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#4DReconstruction #ComputerVision #Transformers #DynamicScenes #DeepLearning

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