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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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#AI #DataScience #MachineLearning #HuggingFace #Research
📝 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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#AI #DataScience #MachineLearning #HuggingFace #Research
📝 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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#AI #DataScience #MachineLearning #HuggingFace #Research
✨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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#AI #DataScience #MachineLearning #HuggingFace #Research
📝 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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✨Reasoning Palette: Modulating Reasoning via Latent Contextualization for Controllable Exploration for (V)LMs
📝 Summary:
Reasoning Palette enhances large language models by using a latent-modulation framework to guide internal planning and improve both inference and reinforcement learning performance. AI-generated summa...
🔹 Publication Date: Published on Dec 19
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.17206
• PDF: https://arxiv.org/pdf/2512.17206
==================================
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📝 Summary:
Reasoning Palette enhances large language models by using a latent-modulation framework to guide internal planning and improve both inference and reinforcement learning performance. AI-generated summa...
🔹 Publication Date: Published on Dec 19
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.17206
• PDF: https://arxiv.org/pdf/2512.17206
==================================
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✨LoGoPlanner: Localization Grounded Navigation Policy with Metric-aware Visual Geometry
📝 Summary:
LoGoPlanner is an end-to-end navigation framework integrating localization, scene geometry, and policy conditioning. It provides implicit state estimation and dense environmental awareness, improving obstacle avoidance and outperforming oracle-localization baselines by over 27 percent.
🔹 Publication Date: Published on Dec 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.19629
• PDF: https://arxiv.org/pdf/2512.19629
==================================
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✓ https://news.1rj.ru/str/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
LoGoPlanner is an end-to-end navigation framework integrating localization, scene geometry, and policy conditioning. It provides implicit state estimation and dense environmental awareness, improving obstacle avoidance and outperforming oracle-localization baselines by over 27 percent.
🔹 Publication Date: Published on Dec 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.19629
• PDF: https://arxiv.org/pdf/2512.19629
==================================
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❤1
✨Infinite-Homography as Robust Conditioning for Camera-Controlled Video Generation
📝 Summary:
InfCam generates high-fidelity videos with accurate camera poses by using infinite homography warping and augmenting synthetic datasets with diverse trajectories. AI-generated summary Recent progress ...
🔹 Publication Date: Published on Dec 18
🔹 Paper Links:
• arXiv Page: https://arxiv.org/pdf/2512.17040
• PDF: https://arxiv.org/pdf/2512.17040
• Project Page: https://emjay73.github.io/InfCam/
• Github: https://github.com/emjay73/InfCam
==================================
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#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
InfCam generates high-fidelity videos with accurate camera poses by using infinite homography warping and augmenting synthetic datasets with diverse trajectories. AI-generated summary Recent progress ...
🔹 Publication Date: Published on Dec 18
🔹 Paper Links:
• arXiv Page: https://arxiv.org/pdf/2512.17040
• PDF: https://arxiv.org/pdf/2512.17040
• Project Page: https://emjay73.github.io/InfCam/
• Github: https://github.com/emjay73/InfCam
==================================
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✨UCoder: Unsupervised Code Generation by Internal Probing of Large Language Models
📝 Summary:
IPC is an unsupervised framework that uses internal probing of large language models to generate code without labeled datasets, achieving competitive performance with reduced resource dependency. AI-g...
🔹 Publication Date: Published on Dec 19
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.17385
• PDF: https://arxiv.org/pdf/2512.17385
==================================
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#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
IPC is an unsupervised framework that uses internal probing of large language models to generate code without labeled datasets, achieving competitive performance with reduced resource dependency. AI-g...
🔹 Publication Date: Published on Dec 19
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.17385
• PDF: https://arxiv.org/pdf/2512.17385
==================================
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✨Brain-Grounded Axes for Reading and Steering LLM States
📝 Summary:
Neurophysiological brain activity is used to create interpretable axes for large language models, enhancing their controllability and interpretability. AI-generated summary Interpretability methods fo...
🔹 Publication Date: Published on Dec 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.19399
• PDF: https://arxiv.org/pdf/2512.19399
• Github: https://github.com/sandroandric/Brain-Grounded-Axes-for-Reading-and-Steering-LLM-States
✨ Spaces citing this paper:
• https://huggingface.co/spaces/AI-nthusiast/cognitive-proxy
==================================
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#AI #DataScience #MachineLearning #HuggingFace #Research
📝 Summary:
Neurophysiological brain activity is used to create interpretable axes for large language models, enhancing their controllability and interpretability. AI-generated summary Interpretability methods fo...
🔹 Publication Date: Published on Dec 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.19399
• PDF: https://arxiv.org/pdf/2512.19399
• Github: https://github.com/sandroandric/Brain-Grounded-Axes-for-Reading-and-Steering-LLM-States
✨ Spaces citing this paper:
• https://huggingface.co/spaces/AI-nthusiast/cognitive-proxy
==================================
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✨Understanding Syllogistic Reasoning in LLMs from Formal and Natural Language Perspectives
📝 Summary:
This study explores syllogistic reasoning in LLMs, examining both symbolic inference and natural language understanding. Some models achieve perfect symbolic performance, leading to questions about whether LLMs are becoming more formal reasoning mechanisms.
🔹 Publication Date: Published on Dec 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.12620
• PDF: https://arxiv.org/pdf/2512.12620
• Github: https://github.com/XAheli/Logic-in-LLMs
==================================
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#LLMs #SyllogisticReasoning #NaturalLanguageProcessing #AIResearch #FormalLogic
📝 Summary:
This study explores syllogistic reasoning in LLMs, examining both symbolic inference and natural language understanding. Some models achieve perfect symbolic performance, leading to questions about whether LLMs are becoming more formal reasoning mechanisms.
🔹 Publication Date: Published on Dec 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.12620
• PDF: https://arxiv.org/pdf/2512.12620
• Github: https://github.com/XAheli/Logic-in-LLMs
==================================
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✨LoPA: Scaling dLLM Inference via Lookahead Parallel Decoding
📝 Summary:
LoPA is a training-free algorithm enhancing dLLM inference parallelism by optimizing Token Filling Order. It achieves 10.1 tokens per forward pass for D2F-Dream, significantly boosting efficiency while maintaining performance. A multi-GPU system further accelerates throughput to 1073.9 tokens per...
🔹 Publication Date: Published on Dec 18
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.16229
• PDF: https://arxiv.org/pdf/2512.16229
• Github: https://zhijie-group.github.io/blogs/lopa
==================================
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#LLM #AI #Inference #ParallelDecoding #Performance
📝 Summary:
LoPA is a training-free algorithm enhancing dLLM inference parallelism by optimizing Token Filling Order. It achieves 10.1 tokens per forward pass for D2F-Dream, significantly boosting efficiency while maintaining performance. A multi-GPU system further accelerates throughput to 1073.9 tokens per...
🔹 Publication Date: Published on Dec 18
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.16229
• PDF: https://arxiv.org/pdf/2512.16229
• Github: https://zhijie-group.github.io/blogs/lopa
==================================
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#LLM #AI #Inference #ParallelDecoding #Performance
✨Does It Tie Out? Towards Autonomous Legal Agents in Venture Capital
📝 Summary:
Automating legal capitalization tie-out in venture capital is difficult for current AI. It requires multi-document reasoning and strict evidence traceability. This paper proposes a world model architecture for automation, advancing applied legal intelligence.
🔹 Publication Date: Published on Dec 21
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.18658
• PDF: https://arxiv.org/pdf/2512.18658
==================================
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#LegalAI #VentureCapital #AIAutomation #LegalTech #ArtificialIntelligence
📝 Summary:
Automating legal capitalization tie-out in venture capital is difficult for current AI. It requires multi-document reasoning and strict evidence traceability. This paper proposes a world model architecture for automation, advancing applied legal intelligence.
🔹 Publication Date: Published on Dec 21
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.18658
• PDF: https://arxiv.org/pdf/2512.18658
==================================
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✨MatSpray: Fusing 2D Material World Knowledge on 3D Geometry
📝 Summary:
MatSpray integrates 2D PBR materials from diffusion models onto 3D Gaussian Splatting geometry. Using projection and neural refinement, it enables accurate relighting and photorealistic rendering from reconstructed scenes. This boosts asset creation efficiency.
🔹 Publication Date: Published on Dec 20
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.18314
• PDF: https://arxiv.org/pdf/2512.18314
• Project Page: https://matspray.jdihlmann.com/
• Github: https://github.com/cgtuebingen/MatSpray
==================================
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#MatSpray #GaussianSplatting #DiffusionModels #3DRendering #ComputerGraphics
📝 Summary:
MatSpray integrates 2D PBR materials from diffusion models onto 3D Gaussian Splatting geometry. Using projection and neural refinement, it enables accurate relighting and photorealistic rendering from reconstructed scenes. This boosts asset creation efficiency.
🔹 Publication Date: Published on Dec 20
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.18314
• PDF: https://arxiv.org/pdf/2512.18314
• Project Page: https://matspray.jdihlmann.com/
• Github: https://github.com/cgtuebingen/MatSpray
==================================
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❤1
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✨CASA: Cross-Attention via Self-Attention for Efficient Vision-Language Fusion
📝 Summary:
CASA enhances cross-attention for vision-language models by adding local text-to-text interaction. This approach substantially reduces the performance gap with costly token insertion methods on detailed visual tasks. CASA maintains efficiency and scalability for long-context multimodal applicatio...
🔹 Publication Date: Published on Dec 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.19535
• PDF: https://arxiv.org/pdf/2512.19535
• Project Page: https://kyutai.org/casa
• Github: https://github.com/kyutai-labs/casa
🔹 Models citing this paper:
• https://huggingface.co/kyutai/CASA-Helium1-VL-2B
✨ Spaces citing this paper:
• https://huggingface.co/spaces/kyutai/casa-samples
==================================
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#VisionLanguage #MultimodalAI #AttentionMechanisms #EfficientAI #DeepLearning
📝 Summary:
CASA enhances cross-attention for vision-language models by adding local text-to-text interaction. This approach substantially reduces the performance gap with costly token insertion methods on detailed visual tasks. CASA maintains efficiency and scalability for long-context multimodal applicatio...
🔹 Publication Date: Published on Dec 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.19535
• PDF: https://arxiv.org/pdf/2512.19535
• Project Page: https://kyutai.org/casa
• Github: https://github.com/kyutai-labs/casa
🔹 Models citing this paper:
• https://huggingface.co/kyutai/CASA-Helium1-VL-2B
✨ Spaces citing this paper:
• https://huggingface.co/spaces/kyutai/casa-samples
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❤3
✨Over++: Generative Video Compositing for Layer Interaction Effects
📝 Summary:
Over++ introduces augmented compositing, a framework that generates realistic, text-prompted environmental effects for videos. It synthesizes effects like shadows onto video layers while preserving the original scene, outperforming prior methods without dense annotations.
🔹 Publication Date: Published on Dec 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.19661
• PDF: https://arxiv.org/pdf/2512.19661
• Project Page: https://overplusplus.github.io/
==================================
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#GenerativeAI #VideoCompositing #VFX #ComputerGraphics #AIResearch
📝 Summary:
Over++ introduces augmented compositing, a framework that generates realistic, text-prompted environmental effects for videos. It synthesizes effects like shadows onto video layers while preserving the original scene, outperforming prior methods without dense annotations.
🔹 Publication Date: Published on Dec 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.19661
• PDF: https://arxiv.org/pdf/2512.19661
• Project Page: https://overplusplus.github.io/
==================================
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👍1
✨SecureCode v2.0: A Production-Grade Dataset for Training Security-Aware Code Generation Models
📝 Summary:
SecureCode v2.0 is a production-grade dataset of 1215 security-focused coding examples. It trains AI models to generate secure code by providing real-incident examples with vulnerable and secure implementations, attacks, defense, and operational security context across 11 languages, using a conve...
🔹 Publication Date: Published on Dec 20
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.18542
• PDF: https://arxiv.org/pdf/2512.18542
• Project Page: https://perfecxion.ai/
• Github: https://github.com/scthornton/securecode-v2
==================================
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#Cybersecurity #CodeSecurity #AI #CodeGeneration #Dataset
📝 Summary:
SecureCode v2.0 is a production-grade dataset of 1215 security-focused coding examples. It trains AI models to generate secure code by providing real-incident examples with vulnerable and secure implementations, attacks, defense, and operational security context across 11 languages, using a conve...
🔹 Publication Date: Published on Dec 20
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.18542
• PDF: https://arxiv.org/pdf/2512.18542
• Project Page: https://perfecxion.ai/
• Github: https://github.com/scthornton/securecode-v2
==================================
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✨Step-DeepResearch Technical Report
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Step-DeepResearch is an end-to-end agent for deep research, using a data synthesis strategy and progressive training. It achieves expert-level capabilities, outperforming existing models and rivaling SOTA closed-source models with cost-efficiency. It also introduces ADR-Bench for realistic Chines...
🔹 Publication Date: Published on Dec 23
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.20491
• PDF: https://arxiv.org/pdf/2512.20491
==================================
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#AI #MachineLearning #DeepResearch #AIagent #SOTA
📝 Summary:
Step-DeepResearch is an end-to-end agent for deep research, using a data synthesis strategy and progressive training. It achieves expert-level capabilities, outperforming existing models and rivaling SOTA closed-source models with cost-efficiency. It also introduces ADR-Bench for realistic Chines...
🔹 Publication Date: Published on Dec 23
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.20491
• PDF: https://arxiv.org/pdf/2512.20491
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#AI #MachineLearning #DeepResearch #AIagent #SOTA
✨Bottom-up Policy Optimization: Your Language Model Policy Secretly Contains Internal Policies
📝 Summary:
This paper decomposes LLM policies into internal layer and modular policies, revealing distinct reasoning patterns across layers. It finds early layers explore and top layers refine. Motivated by this, Bottom-up Policy Optimization BuPO is proposed to optimize internal layer policies for superior...
🔹 Publication Date: Published on Dec 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.19673
• PDF: https://arxiv.org/pdf/2512.19673
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For more data science resources:
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#LLM #PolicyOptimization #DeepLearning #AIResearch #NLP
📝 Summary:
This paper decomposes LLM policies into internal layer and modular policies, revealing distinct reasoning patterns across layers. It finds early layers explore and top layers refine. Motivated by this, Bottom-up Policy Optimization BuPO is proposed to optimize internal layer policies for superior...
🔹 Publication Date: Published on Dec 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.19673
• PDF: https://arxiv.org/pdf/2512.19673
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For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT
#LLM #PolicyOptimization #DeepLearning #AIResearch #NLP