✨FAMA: Failure-Aware Meta-Agentic Framework for Open-Source LLMs in Interactive Tool Use Environments

📝 Summary:
Failure-Aware Meta-Agentic framework improves open-source LLM performance in conversational scenarios by identifying common errors and deploying specialized agents to correct them. AI-generated summar...

🔹 Publication Date: Published on Apr 28

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.25135
• PDF: https://arxiv.org/pdf/2604.25135

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✨Operating-Layer Controls for Onchain Language-Model Agents Under Real Capital

📝 Summary:
Autonomous language-model agents managing real cryptocurrency trades demonstrated high reliability through comprehensive system design encompassing prompt compilation, policy validation, and execution...

🔹 Publication Date: Published on Apr 28

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.26091
• PDF: https://arxiv.org/pdf/2604.26091
• Project Page: https://www.dxrg.ai/

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✨Enhanced Privacy and Communication Efficiency in Non-IID Federated Learning with Adaptive Quantization and Differential Privacy

📝 Summary:
Adaptive quantization combined with differential privacy reduces communication overhead in federated learning while maintaining model accuracy and privacy guarantees. AI-generated summary Federated le...

🔹 Publication Date: Published on Apr 25

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.23426
• PDF: https://arxiv.org/pdf/2604.23426
• Github: https://github.com/eardic/FL_DPQS

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✨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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