✨Sample Selection Using Multi-Task Autoencoders in Federated Learning with Non-IID Data

📝 Summary:
Federated learning sample selection methods using multitask autoencoders, outlier detection techniques, and deep support vector data description enhance model accuracy under non-IID and noisy conditio...

🔹 Publication Date: Published on Apr 28

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.26116
• PDF: https://arxiv.org/pdf/2604.26116
• Project Page: https://github.com/eardic/FL_DPQS

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✨Synthetic Computers at Scale for Long-Horizon Productivity Simulation

📝 Summary:
Synthetic Computers at Scale creates realistic computer environments with folders and content. This enables long-horizon productivity simulations for AI agents, improving their performance through experiential learning and scalable self-improvement.

🔹 Publication Date: Published on Apr 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.28181
• PDF: https://arxiv.org/pdf/2604.28181
• Project Page: https://huggingface.co/datasets/microsoft/synthetic-computers-at-scale

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✨Heterogeneous Scientific Foundation Model Collaboration

📝 Summary:
Eywa is a heterogeneous agentic framework that extends language-centric systems to scientific foundation models by integrating domain-specific models with language-based reasoning interfaces for impro...

🔹 Publication Date: Published on Apr 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.27351
• PDF: https://arxiv.org/pdf/2604.27351
• Project Page: https://www.zihao.website/eywa.github.io/
• Github: https://www.zihao.website/eywa.github.io/

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✨Visual Generation in the New Era: An Evolution from Atomic Mapping to Agentic World Modeling

📝 Summary:
Visual generation models need to advance beyond appearance synthesis to incorporate structural, dynamic, and causal understanding through a five-level taxonomy spanning from atomic to world-modeling g...

🔹 Publication Date: Published on Apr 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.28185
• PDF: https://arxiv.org/pdf/2604.28185

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✨Intern-Atlas: A Methodological Evolution Graph as Research Infrastructure for AI Scientists

📝 Summary:
Intern-Atlas presents a methodological evolution graph that captures structured relationships between research methods across AI literature, enabling automated tracking of methodological development a...

🔹 Publication Date: Published on Apr 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.28158
• PDF: https://arxiv.org/pdf/2604.28158
• Project Page: https://intern-atlas.opendatalab.org.cn/

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✨Representation Fréchet Loss for Visual Generation

📝 Summary:
Fréchet Distance can be effectively optimized as a training objective when decoupling population size from batch size, leading to improved generator quality and alternative evaluation metrics. AI-gene...

🔹 Publication Date: Published on Apr 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.28190
• PDF: https://arxiv.org/pdf/2604.28190
• Github: https://github.com/Jiawei-Yang/FD-Loss

🔹 Models citing this paper:
• https://huggingface.co/jjiaweiyang/FD-Loss

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✨World2Minecraft: Occupancy-Driven Simulated Scenes Construction

📝 Summary:
World2Minecraft converts real-world scenes into structured Minecraft environments using 3D semantic occupancy prediction, with MinecraftOcc dataset enhancing occupancy prediction benchmarks for embodi...

🔹 Publication Date: Published on Apr 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.27578
• PDF: https://arxiv.org/pdf/2604.27578
• Project Page: https://world2minecraft.github.io/
• Github: https://github.com/Nepenthes-zlc/World2Minecraft

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✨The Last Human-Written Paper: Agent-Native Research Artifacts

📝 Summary:
S c i e n t i f i c p u b l i c a t i o n c o m p r e s s e s a b r a n c h i n g , i t e r a t i v e r e s e a r c h p r o c e s s i n t o a l i n e a r n a r r a t i v e , d i s c a r d i n g t h e ...

🔹 Publication Date: Published on Apr 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.24658
• PDF: https://arxiv.org/pdf/2604.24658
• Project Page: https://www.orchestra-research.com/ara
• Github: https://github.com/Orchestra-Research/Agent-Native-Research-Artifact

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✨MoCapAnything V2: End-to-End Motion Capture for Arbitrary Skeletons

📝 Summary:
A fully end-to-end framework for arbitrary-skeleton motion capture that jointly optimizes video-to-pose and pose-to-rotation prediction while addressing rotation ambiguity through reference pose-rotat...

🔹 Publication Date: Published on Apr 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.28130
• PDF: https://arxiv.org/pdf/2604.28130
• Project Page: https://animotionlab.github.io/MoCapAnythingV2/
• Github: https://github.com/animotionlab26/MocapAnything

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✨PhyCo: Learning Controllable Physical Priors for Generative Motion

📝 Summary:
PhyCo enhances video diffusion models with physics-based control through a large-scale dataset, physics-supervised fine-tuning, and vision-language model guidance for improved physical consistency. AI...

🔹 Publication Date: Published on Apr 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.28169
• PDF: https://arxiv.org/pdf/2604.28169
• Project Page: https://phyco-video.github.io/

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

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