✨PDFMathTranslate: Scientific Document Translation Preserving Layouts
📝 Summary:
PDFMathTranslate is an open-source software that translates scientific documents while maintaining layout integrity, utilizing advancements in large language models and layout detection. AI-generated ...
🔹 Publication Date: Published on Jul 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2507.03009
• PDF: https://arxiv.org/pdf/2507.03009
• Github: https://github.com/byaidu/pdfmathtranslate
==================================
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📝 Summary:
PDFMathTranslate is an open-source software that translates scientific documents while maintaining layout integrity, utilizing advancements in large language models and layout detection. AI-generated ...
🔹 Publication Date: Published on Jul 2
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2507.03009
• PDF: https://arxiv.org/pdf/2507.03009
• Github: https://github.com/byaidu/pdfmathtranslate
==================================
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✨GlobalBuildingAtlas: An Open Global and Complete Dataset of Building Polygons, Heights and LoD1 3D Models
📝 Summary:
We introduce GlobalBuildingAtlas, a publicly available dataset providing global and complete coverage of building polygons, heights and Level of Detail 1 (LoD1) 3D building models. This is the first o...
🔹 Publication Date: Published on Jun 4
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2506.04106
• PDF: https://arxiv.org/pdf/2506.04106
• Project Page: https://mediatum.ub.tum.de/1782307
• Github: https://github.com/zhu-xlab/GlobalBuildingAtlas
==================================
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📝 Summary:
We introduce GlobalBuildingAtlas, a publicly available dataset providing global and complete coverage of building polygons, heights and Level of Detail 1 (LoD1) 3D building models. This is the first o...
🔹 Publication Date: Published on Jun 4
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2506.04106
• PDF: https://arxiv.org/pdf/2506.04106
• Project Page: https://mediatum.ub.tum.de/1782307
• Github: https://github.com/zhu-xlab/GlobalBuildingAtlas
==================================
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✨GenieDrive: Towards Physics-Aware Driving World Model with 4D Occupancy Guided Video Generation
📝 Summary:
GenieDrive uses a 4D occupancy-based approach with a VAE and Mutual Control Attention for physics-aware driving video generation, improving forecasting accuracy and video quality. AI-generated summary...
🔹 Publication Date: Published on Dec 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.12751
• PDF: https://arxiv.org/pdf/2512.12751
==================================
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📝 Summary:
GenieDrive uses a 4D occupancy-based approach with a VAE and Mutual Control Attention for physics-aware driving video generation, improving forecasting accuracy and video quality. AI-generated summary...
🔹 Publication Date: Published on Dec 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.12751
• PDF: https://arxiv.org/pdf/2512.12751
==================================
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✨Few-Step Distillation for Text-to-Image Generation: A Practical Guide
📝 Summary:
A systematic study adapts diffusion distillation techniques to text-to-image generation, providing guidelines for successful implementation and deployment. AI-generated summary Diffusion distillation ...
🔹 Publication Date: Published on Dec 15
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13006
• PDF: https://arxiv.org/pdf/2512.13006
• Github: https://github.com/alibaba-damo-academy/T2I-Distill.git
==================================
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📝 Summary:
A systematic study adapts diffusion distillation techniques to text-to-image generation, providing guidelines for successful implementation and deployment. AI-generated summary Diffusion distillation ...
🔹 Publication Date: Published on Dec 15
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13006
• PDF: https://arxiv.org/pdf/2512.13006
• Github: https://github.com/alibaba-damo-academy/T2I-Distill.git
==================================
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✨CAPTAIN: Semantic Feature Injection for Memorization Mitigation in Text-to-Image Diffusion Models
📝 Summary:
CAPTAIN, a training-free framework, mitigates memorization in diffusion models by modifying latent features during denoising, ensuring prompt fidelity and visual quality. AI-generated summary Diffusio...
🔹 Publication Date: Published on Dec 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.10655
• PDF: https://arxiv.org/pdf/2512.10655
==================================
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📝 Summary:
CAPTAIN, a training-free framework, mitigates memorization in diffusion models by modifying latent features during denoising, ensuring prompt fidelity and visual quality. AI-generated summary Diffusio...
🔹 Publication Date: Published on Dec 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.10655
• PDF: https://arxiv.org/pdf/2512.10655
==================================
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✨State over Tokens: Characterizing the Role of Reasoning Tokens
📝 Summary:
The State over Tokens (SoT) framework reinterprets reasoning tokens in large language models as computational states rather than linguistic narratives, highlighting the need for a new focus in researc...
🔹 Publication Date: Published on Dec 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.12777
• PDF: https://arxiv.org/pdf/2512.12777
==================================
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📝 Summary:
The State over Tokens (SoT) framework reinterprets reasoning tokens in large language models as computational states rather than linguistic narratives, highlighting the need for a new focus in researc...
🔹 Publication Date: Published on Dec 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.12777
• PDF: https://arxiv.org/pdf/2512.12777
==================================
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✨From Benchmarks to Business Impact: Deploying IBM Generalist Agent in Enterprise Production
📝 Summary:
IBM's CUGA, a generalist agent with a hierarchical planner-executor architecture, demonstrates state-of-the-art performance in academic benchmarks and shows potential for enterprise adoption in busine...
🔹 Publication Date: Published on Oct 27
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.23856
• PDF: https://arxiv.org/pdf/2510.23856
• Github: https://github.com/cuga-project/cuga-agent
==================================
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📝 Summary:
IBM's CUGA, a generalist agent with a hierarchical planner-executor architecture, demonstrates state-of-the-art performance in academic benchmarks and shows potential for enterprise adoption in busine...
🔹 Publication Date: Published on Oct 27
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.23856
• PDF: https://arxiv.org/pdf/2510.23856
• Github: https://github.com/cuga-project/cuga-agent
==================================
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✨E-RayZer: Self-supervised 3D Reconstruction as Spatial Visual Pre-training
📝 Summary:
E-RayZer is a self-supervised 3D Vision model that directly learns 3D-aware representations from unlabeled images, outperforming existing models in pose estimation and 3D reconstruction tasks. AI-gene...
🔹 Publication Date: Published on Dec 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.10950
• PDF: https://arxiv.org/pdf/2512.10950
• Project Page: https://qitaozhao.github.io/E-RayZer
• Github: https://github.com/QitaoZhao/E-RayZer
==================================
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📝 Summary:
E-RayZer is a self-supervised 3D Vision model that directly learns 3D-aware representations from unlabeled images, outperforming existing models in pose estimation and 3D reconstruction tasks. AI-gene...
🔹 Publication Date: Published on Dec 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.10950
• PDF: https://arxiv.org/pdf/2512.10950
• Project Page: https://qitaozhao.github.io/E-RayZer
• Github: https://github.com/QitaoZhao/E-RayZer
==================================
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✨Flowception: Temporally Expansive Flow Matching for Video Generation
📝 Summary:
Flowception, a non-autoregressive video generation framework, interleaves discrete frame insertions with continuous denoising, improving efficiency and performance over existing methods. AI-generated ...
🔹 Publication Date: Published on Dec 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.11438
• PDF: https://arxiv.org/pdf/2512.11438
• Project Page: https://flowception-meta.github.io/
==================================
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📝 Summary:
Flowception, a non-autoregressive video generation framework, interleaves discrete frame insertions with continuous denoising, improving efficiency and performance over existing methods. AI-generated ...
🔹 Publication Date: Published on Dec 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.11438
• PDF: https://arxiv.org/pdf/2512.11438
• Project Page: https://flowception-meta.github.io/
==================================
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✨Rethinking Expert Trajectory Utilization in LLM Post-training
📝 Summary:
The Sequential SFT-then-RL pipeline is identified as optimal for integrating expert trajectories, with guidelines for scaling and trajectory selection based on performance metrics. AI-generated summar...
🔹 Publication Date: Published on Dec 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.11470
• PDF: https://arxiv.org/pdf/2512.11470
• Github: https://github.com/LINs-lab/RETU
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📝 Summary:
The Sequential SFT-then-RL pipeline is identified as optimal for integrating expert trajectories, with guidelines for scaling and trajectory selection based on performance metrics. AI-generated summar...
🔹 Publication Date: Published on Dec 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.11470
• PDF: https://arxiv.org/pdf/2512.11470
• Github: https://github.com/LINs-lab/RETU
==================================
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✨FoundationMotion: Auto-Labeling and Reasoning about Spatial Movement in Videos
📝 Summary:
FoundationMotion is an automated pipeline for creating large-scale motion datasets using object detection, trajectory extraction, and LLM-generated captions, improving motion understanding in models. ...
🔹 Publication Date: Published on Dec 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.10927
• PDF: https://arxiv.org/pdf/2512.10927
• Project Page: https://yulugan.com/projects/FoundationMotion.html
• Github: https://github.com/Wolfv0/FoundationMotion/tree/main
==================================
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📝 Summary:
FoundationMotion is an automated pipeline for creating large-scale motion datasets using object detection, trajectory extraction, and LLM-generated captions, improving motion understanding in models. ...
🔹 Publication Date: Published on Dec 11
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.10927
• PDF: https://arxiv.org/pdf/2512.10927
• Project Page: https://yulugan.com/projects/FoundationMotion.html
• Github: https://github.com/Wolfv0/FoundationMotion/tree/main
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✨KD-OCT: Efficient Knowledge Distillation for Clinical-Grade Retinal OCT Classification
📝 Summary:
A novel knowledge distillation framework compresses a high-performance ConvNeXtV2-Large model into a lightweight EfficientNet-B2 for efficient AMD and CNV classification in real-time clinical settings...
🔹 Publication Date: Published on Dec 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.09069
• PDF: https://arxiv.org/pdf/2512.09069
• Github: https://github.com/erfan-nourbakhsh/KD-OCT
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📝 Summary:
A novel knowledge distillation framework compresses a high-performance ConvNeXtV2-Large model into a lightweight EfficientNet-B2 for efficient AMD and CNV classification in real-time clinical settings...
🔹 Publication Date: Published on Dec 9
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.09069
• PDF: https://arxiv.org/pdf/2512.09069
• Github: https://github.com/erfan-nourbakhsh/KD-OCT
==================================
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