✨HERBench: A Benchmark for Multi-Evidence Integration in Video Question Answering
📝 Summary:
HERBench is a new VideoQA benchmark designed to test multi-evidence integration across time, revealing significant challenges for current Video-LLMs. It requires models to fuse at least three visual cues from distinct segments, with state-of-the-art models performing poorly due to retrieval and f...
🔹 Publication Date: Published on Dec 16
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.14870
• PDF: https://arxiv.org/pdf/2512.14870
• Project Page: https://herbench.github.io/
• Github: https://github.com/DanBenAmi/HERBench
✨ Datasets citing this paper:
• https://huggingface.co/datasets/DanBenAmi/HERBench
==================================
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#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
HERBench is a new VideoQA benchmark designed to test multi-evidence integration across time, revealing significant challenges for current Video-LLMs. It requires models to fuse at least three visual cues from distinct segments, with state-of-the-art models performing poorly due to retrieval and f...
🔹 Publication Date: Published on Dec 16
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.14870
• PDF: https://arxiv.org/pdf/2512.14870
• Project Page: https://herbench.github.io/
• Github: https://github.com/DanBenAmi/HERBench
✨ Datasets citing this paper:
• https://huggingface.co/datasets/DanBenAmi/HERBench
==================================
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#AI #DataScience #MachineLearning #HuggingFace #Research
❤2
✨An Anatomy of Vision-Language-Action Models: From Modules to Milestones and Challenges
📝 Summary:
This survey offers a structured guide to Vision-Language-Action VLA models in robotics. It breaks down five key challenges: representation, execution, generalization, safety, and datasets, serving as a roadmap for researchers.
🔹 Publication Date: Published on Dec 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.11362
• PDF: https://arxiv.org/pdf/2512.11362
• Project Page: https://suyuz1.github.io/Survery/
• Github: https://suyuz1.github.io/VLA-Survey-Anatomy/
==================================
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#VLAModels #Robotics #ArtificialIntelligence #VisionLanguage #AIResearch
📝 Summary:
This survey offers a structured guide to Vision-Language-Action VLA models in robotics. It breaks down five key challenges: representation, execution, generalization, safety, and datasets, serving as a roadmap for researchers.
🔹 Publication Date: Published on Dec 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.11362
• PDF: https://arxiv.org/pdf/2512.11362
• Project Page: https://suyuz1.github.io/Survery/
• Github: https://suyuz1.github.io/VLA-Survey-Anatomy/
==================================
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#VLAModels #Robotics #ArtificialIntelligence #VisionLanguage #AIResearch
❤1
✨RadarGen: Automotive Radar Point Cloud Generation from Cameras
📝 Summary:
RadarGen synthesizes realistic automotive radar point clouds from camera images using diffusion models. It incorporates depth, semantic, and motion cues for physical plausibility, enabling scalable multimodal simulation and improving perception models.
🔹 Publication Date: Published on Dec 19
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.17897
• PDF: https://arxiv.org/pdf/2512.17897
==================================
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#AutomotiveRadar #PointClouds #DiffusionModels #ComputerVision #AutonomousDriving
📝 Summary:
RadarGen synthesizes realistic automotive radar point clouds from camera images using diffusion models. It incorporates depth, semantic, and motion cues for physical plausibility, enabling scalable multimodal simulation and improving perception models.
🔹 Publication Date: Published on Dec 19
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.17897
• PDF: https://arxiv.org/pdf/2512.17897
==================================
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#AutomotiveRadar #PointClouds #DiffusionModels #ComputerVision #AutonomousDriving
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✨3D-RE-GEN: 3D Reconstruction of Indoor Scenes with a Generative Framework
📝 Summary:
3D-RE-GEN reconstructs single images into modifiable 3D textured mesh scenes with comprehensive backgrounds. It uses a compositional generative framework and novel optimization for artist-ready, physically realistic layouts, achieving state-of-the-art performance.
🔹 Publication Date: Published on Dec 19
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.17459
• PDF: https://arxiv.org/pdf/2512.17459
• Project Page: https://3dregen.jdihlmann.com/
• Github: https://github.com/cgtuebingen/3D-RE-GEN
==================================
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#3DReconstruction #GenerativeAI #ComputerVision #DeepLearning #ComputerGraphics
📝 Summary:
3D-RE-GEN reconstructs single images into modifiable 3D textured mesh scenes with comprehensive backgrounds. It uses a compositional generative framework and novel optimization for artist-ready, physically realistic layouts, achieving state-of-the-art performance.
🔹 Publication Date: Published on Dec 19
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.17459
• PDF: https://arxiv.org/pdf/2512.17459
• Project Page: https://3dregen.jdihlmann.com/
• Github: https://github.com/cgtuebingen/3D-RE-GEN
==================================
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#3DReconstruction #GenerativeAI #ComputerVision #DeepLearning #ComputerGraphics
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✨Meta-RL Induces Exploration in Language Agents
📝 Summary:
LaMer, a Meta-RL framework, enhances LLM agents exploration and adaptation in RL tasks. It significantly improves their performance and generalization across diverse environments, proving Meta-RLs effectiveness for robust adaptation in language agents.
🔹 Publication Date: Published on Dec 18
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.16848
• PDF: https://arxiv.org/pdf/2512.16848
==================================
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#MetaRL #LLMAgents #ReinforcementLearning #NLP #AI
📝 Summary:
LaMer, a Meta-RL framework, enhances LLM agents exploration and adaptation in RL tasks. It significantly improves their performance and generalization across diverse environments, proving Meta-RLs effectiveness for robust adaptation in language agents.
🔹 Publication Date: Published on Dec 18
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.16848
• PDF: https://arxiv.org/pdf/2512.16848
==================================
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#MetaRL #LLMAgents #ReinforcementLearning #NLP #AI
✨A Benchmark and Agentic Framework for Omni-Modal Reasoning and Tool Use in Long Videos
📝 Summary:
This paper introduces LongShOTBench, a diagnostic benchmark for long-form multimodal video understanding with open-ended questions and agentic tool use. It also presents LongShOTAgent, an agentic system for video analysis. Results show state-of-the-art models struggle significantly, highlighting ...
🔹 Publication Date: Published on Dec 18
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.16978
• PDF: https://arxiv.org/pdf/2512.16978
• Project Page: https://mbzuai-oryx.github.io/LongShOT/
• Github: https://github.com/mbzuai-oryx/longshot
✨ Datasets citing this paper:
• https://huggingface.co/datasets/MBZUAI/longshot-bench
==================================
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#VideoAI #MultimodalAI #AgenticAI #AIbenchmark #AIResearch
📝 Summary:
This paper introduces LongShOTBench, a diagnostic benchmark for long-form multimodal video understanding with open-ended questions and agentic tool use. It also presents LongShOTAgent, an agentic system for video analysis. Results show state-of-the-art models struggle significantly, highlighting ...
🔹 Publication Date: Published on Dec 18
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.16978
• PDF: https://arxiv.org/pdf/2512.16978
• Project Page: https://mbzuai-oryx.github.io/LongShOT/
• Github: https://github.com/mbzuai-oryx/longshot
✨ Datasets citing this paper:
• https://huggingface.co/datasets/MBZUAI/longshot-bench
==================================
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#VideoAI #MultimodalAI #AgenticAI #AIbenchmark #AIResearch
✨MineTheGap: Automatic Mining of Biases in Text-to-Image Models
📝 Summary:
MineTheGap automatically finds prompts that cause Text-to-Image models to generate biased outputs. It uses a genetic algorithm and a novel bias score to identify and rank biases, aiming to reduce redundancy and improve output diversity.
🔹 Publication Date: Published on Dec 15
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13427
• PDF: https://arxiv.org/pdf/2512.13427
==================================
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#AIbias #TextToImage #GenerativeAI #ResponsibleAI #MachineLearning
📝 Summary:
MineTheGap automatically finds prompts that cause Text-to-Image models to generate biased outputs. It uses a genetic algorithm and a novel bias score to identify and rank biases, aiming to reduce redundancy and improve output diversity.
🔹 Publication Date: Published on Dec 15
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13427
• PDF: https://arxiv.org/pdf/2512.13427
==================================
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#AIbias #TextToImage #GenerativeAI #ResponsibleAI #MachineLearning
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✨Bolmo: Byteifying the Next Generation of Language Models
📝 Summary:
Bolmo introduces competitive byte-level language models by efficiently converting existing subword models. This byteification overcomes subword limitations, matching performance with minimal training. Bolmo makes byte-level LMs practical.
🔹 Publication Date: Published on Dec 17
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.15586
• PDF: https://arxiv.org/pdf/2512.15586
🔹 Models citing this paper:
• https://huggingface.co/allenai/Bolmo-7B
• https://huggingface.co/allenai/Bolmo-1B
✨ Datasets citing this paper:
• https://huggingface.co/datasets/allenai/bolmo_mix
==================================
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#LanguageModels #ByteLevelLMs #NLP #DeepLearning #AIResearch
📝 Summary:
Bolmo introduces competitive byte-level language models by efficiently converting existing subword models. This byteification overcomes subword limitations, matching performance with minimal training. Bolmo makes byte-level LMs practical.
🔹 Publication Date: Published on Dec 17
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.15586
• PDF: https://arxiv.org/pdf/2512.15586
🔹 Models citing this paper:
• https://huggingface.co/allenai/Bolmo-7B
• https://huggingface.co/allenai/Bolmo-1B
✨ Datasets citing this paper:
• https://huggingface.co/datasets/allenai/bolmo_mix
==================================
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#LanguageModels #ByteLevelLMs #NLP #DeepLearning #AIResearch
❤1
✨DataFlow: An LLM-Driven Framework for Unified Data Preparation and Workflow Automation in the Era of Data-Centric AI
📝 Summary:
DataFlow is an LLM-driven framework for unified, high-quality data preparation. It automates pipeline generation from natural language, significantly boosting LLM performance across diverse tasks like math, code, and text. DataFlow ensures reproducible data and provides a scalable foundation for AI.
🔹 Publication Date: Published on Dec 18
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.16676
• PDF: https://arxiv.org/pdf/2512.16676
• Project Page: https://github.com/OpenDCAI/DataFlow
• Github: https://github.com/OpenDCAI/DataFlow
✨ Datasets citing this paper:
• https://huggingface.co/datasets/OpenDCAI/dataflow-demo-code
• https://huggingface.co/datasets/OpenDCAI/dataflow-demo-Text2SQL
• https://huggingface.co/datasets/OpenDCAI/dataflow-instruct-10k
==================================
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#LLM #DataPreparation #DataCentricAI #WorkflowAutomation #AIResearch
📝 Summary:
DataFlow is an LLM-driven framework for unified, high-quality data preparation. It automates pipeline generation from natural language, significantly boosting LLM performance across diverse tasks like math, code, and text. DataFlow ensures reproducible data and provides a scalable foundation for AI.
🔹 Publication Date: Published on Dec 18
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.16676
• PDF: https://arxiv.org/pdf/2512.16676
• Project Page: https://github.com/OpenDCAI/DataFlow
• Github: https://github.com/OpenDCAI/DataFlow
✨ Datasets citing this paper:
• https://huggingface.co/datasets/OpenDCAI/dataflow-demo-code
• https://huggingface.co/datasets/OpenDCAI/dataflow-demo-Text2SQL
• https://huggingface.co/datasets/OpenDCAI/dataflow-instruct-10k
==================================
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#LLM #DataPreparation #DataCentricAI #WorkflowAutomation #AIResearch
arXiv.org
DataFlow: An LLM-Driven Framework for Unified Data Preparation and...
The rapidly growing demand for high-quality data in Large Language Models (LLMs) has intensified the need for scalable, reliable, and semantically rich data preparation pipelines. However, current...
✨Can LLMs Estimate Student Struggles? Human-AI Difficulty Alignment with Proficiency Simulation for Item Difficulty Prediction
📝 Summary:
LLMs poorly estimate human cognitive difficulty for educational tasks. Scaling models does not improve alignment with humans; they converge to a machine consensus and fail to simulate student struggles or show introspection.
🔹 Publication Date: Published on Dec 21
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.18880
• PDF: https://arxiv.org/pdf/2512.18880
• Github: https://github.com/MingLiiii/Difficulty_Alignment
==================================
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#LLM #EducationalAI #ItemDifficulty #HumanAIAlignment #AIResearch
📝 Summary:
LLMs poorly estimate human cognitive difficulty for educational tasks. Scaling models does not improve alignment with humans; they converge to a machine consensus and fail to simulate student struggles or show introspection.
🔹 Publication Date: Published on Dec 21
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.18880
• PDF: https://arxiv.org/pdf/2512.18880
• Github: https://github.com/MingLiiii/Difficulty_Alignment
==================================
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✨The Prism Hypothesis: Harmonizing Semantic and Pixel Representations via Unified Autoencoding
📝 Summary:
The Prism Hypothesis posits semantic encoders capture low-frequency meaning, while pixel encoders retain high-frequency details. Unified Autoencoding UAE leverages this with a frequency-band modulator to harmonize both into a single latent space. This achieves state-of-the-art performance on imag...
🔹 Publication Date: Published on Dec 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.19693
• PDF: https://arxiv.org/pdf/2512.19693
• Github: https://github.com/WeichenFan/UAE
==================================
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#DeepLearning #ComputerVision #Autoencoders #RepresentationLearning #AIResearch
📝 Summary:
The Prism Hypothesis posits semantic encoders capture low-frequency meaning, while pixel encoders retain high-frequency details. Unified Autoencoding UAE leverages this with a frequency-band modulator to harmonize both into a single latent space. This achieves state-of-the-art performance on imag...
🔹 Publication Date: Published on Dec 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.19693
• PDF: https://arxiv.org/pdf/2512.19693
• Github: https://github.com/WeichenFan/UAE
==================================
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#DeepLearning #ComputerVision #Autoencoders #RepresentationLearning #AIResearch
✨GenEnv: Difficulty-Aligned Co-Evolution Between LLM Agents and Environment Simulators
📝 Summary:
GenEnv, a framework using a co-evolutionary game with a generative environment simulator, enhances LLM agent performance by 40.3% over 7B baselines and uses less data than offline augmentation. AI-gen...
🔹 Publication Date: Published on Dec 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.19682
• PDF: https://arxiv.org/pdf/2512.19682
• Github: https://github.com/Gen-Verse/GenEnv
==================================
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#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
GenEnv, a framework using a co-evolutionary game with a generative environment simulator, enhances LLM agent performance by 40.3% over 7B baselines and uses less data than offline augmentation. AI-gen...
🔹 Publication Date: Published on Dec 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.19682
• PDF: https://arxiv.org/pdf/2512.19682
• Github: https://github.com/Gen-Verse/GenEnv
==================================
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✨StoryMem: Multi-shot Long Video Storytelling with Memory
📝 Summary:
StoryMem enhances multi-shot video generation with cinematic quality and long-range consistency using a memory bank and pre-trained single-shot video diffusion models. AI-generated summary Visual stor...
🔹 Publication Date: Published on Dec 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.19539
• PDF: https://arxiv.org/pdf/2512.19539
==================================
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#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
StoryMem enhances multi-shot video generation with cinematic quality and long-range consistency using a memory bank and pre-trained single-shot video diffusion models. AI-generated summary Visual stor...
🔹 Publication Date: Published on Dec 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.19539
• PDF: https://arxiv.org/pdf/2512.19539
==================================
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#AI #DataScience #MachineLearning #HuggingFace #Research
✨MobileWorld: Benchmarking Autonomous Mobile Agents in Agent-User Interactive, and MCP-Augmented Environments
📝 Summary:
MobileWorld, a more challenging benchmark than AndroidWorld, includes diverse real-world mobile tasks and interactions, revealing significant gaps in current model capabilities. AI-generated summary A...
🔹 Publication Date: Published on Dec 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.19432
• PDF: https://arxiv.org/pdf/2512.19432
==================================
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#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
MobileWorld, a more challenging benchmark than AndroidWorld, includes diverse real-world mobile tasks and interactions, revealing significant gaps in current model capabilities. AI-generated summary A...
🔹 Publication Date: Published on Dec 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.19432
• PDF: https://arxiv.org/pdf/2512.19432
==================================
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✨Name That Part: 3D Part Segmentation and Naming
📝 Summary:
ALIGN-Parts addresses semantic 3D part segmentation by aligning implicit 3D part representations with part denoscriptions using geometric, appearance, and semantic cues, supporting open-vocabulary part ...
🔹 Publication Date: Published on Dec 19
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.18003
• PDF: https://arxiv.org/pdf/2512.18003
• Project Page: https://name-that-part.github.io/
==================================
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#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
ALIGN-Parts addresses semantic 3D part segmentation by aligning implicit 3D part representations with part denoscriptions using geometric, appearance, and semantic cues, supporting open-vocabulary part ...
🔹 Publication Date: Published on Dec 19
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.18003
• PDF: https://arxiv.org/pdf/2512.18003
• Project Page: https://name-that-part.github.io/
==================================
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#AI #DataScience #MachineLearning #HuggingFace #Research
✨QuCo-RAG: Quantifying Uncertainty from the Pre-training Corpus for Dynamic Retrieval-Augmented Generation
📝 Summary:
QuCo-RAG uses objective corpus statistics to mitigate hallucinations in large language models during generation, improving accuracy across various benchmarks. AI-generated summary Dynamic Retrieval-Au...
🔹 Publication Date: Published on Dec 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.19134
• PDF: https://arxiv.org/pdf/2512.19134
==================================
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📝 Summary:
QuCo-RAG uses objective corpus statistics to mitigate hallucinations in large language models during generation, improving accuracy across various benchmarks. AI-generated summary Dynamic Retrieval-Au...
🔹 Publication Date: Published on Dec 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.19134
• PDF: https://arxiv.org/pdf/2512.19134
==================================
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✨Region-Constraint In-Context Generation for Instructional Video Editing
📝 Summary:
ReCo is a novel instructional video editing paradigm that enhances accuracy and reduces token interference by incorporating constraint modeling and regularization techniques during in-context generati...
🔹 Publication Date: Published on Dec 19
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.17650
• PDF: https://arxiv.org/pdf/2512.17650
• Project Page: https://zhw-zhang.github.io/ReCo-page/
• Github: https://github.com/HiDream-ai/ReCo
✨ Datasets citing this paper:
• https://huggingface.co/datasets/HiDream-ai/ReCo-Data
==================================
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📝 Summary:
ReCo is a novel instructional video editing paradigm that enhances accuracy and reduces token interference by incorporating constraint modeling and regularization techniques during in-context generati...
🔹 Publication Date: Published on Dec 19
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.17650
• PDF: https://arxiv.org/pdf/2512.17650
• Project Page: https://zhw-zhang.github.io/ReCo-page/
• Github: https://github.com/HiDream-ai/ReCo
✨ Datasets citing this paper:
• https://huggingface.co/datasets/HiDream-ai/ReCo-Data
==================================
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✨WorldWarp: Propagating 3D Geometry with Asynchronous Video Diffusion
📝 Summary:
WorldWarp addresses the challenge of generating consistent long-range videos by integrating a 3D geometric cache with a spatio-temporal diffusion model, ensuring structural consistency and textural re...
🔹 Publication Date: Published on Dec 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.19678
• PDF: https://arxiv.org/pdf/2512.19678
• Project Page: https://hyokong.github.io/worldwarp-page/
• Github: https://hyokong.github.io/worldwarp-page/
🔹 Models citing this paper:
• https://huggingface.co/imsuperkong/worldwarp
==================================
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📝 Summary:
WorldWarp addresses the challenge of generating consistent long-range videos by integrating a 3D geometric cache with a spatio-temporal diffusion model, ensuring structural consistency and textural re...
🔹 Publication Date: Published on Dec 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.19678
• PDF: https://arxiv.org/pdf/2512.19678
• Project Page: https://hyokong.github.io/worldwarp-page/
• Github: https://hyokong.github.io/worldwarp-page/
🔹 Models citing this paper:
• https://huggingface.co/imsuperkong/worldwarp
==================================
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✨Real2Edit2Real: Generating Robotic Demonstrations via a 3D Control Interface
📝 Summary:
A framework called Real2Edit2Real generates new manipulation demonstrations by using 3D reconstruction, editing, and video synthesis, improving data efficiency in robot learning. AI-generated summary ...
🔹 Publication Date: Published on Dec 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.19402
• PDF: https://arxiv.org/pdf/2512.19402
• Github: https://real2edit2real.github.io/
==================================
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📝 Summary:
A framework called Real2Edit2Real generates new manipulation demonstrations by using 3D reconstruction, editing, and video synthesis, improving data efficiency in robot learning. AI-generated summary ...
🔹 Publication Date: Published on Dec 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.19402
• PDF: https://arxiv.org/pdf/2512.19402
• Github: https://real2edit2real.github.io/
==================================
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