🔹 Title: FAPO: Flawed-Aware Policy Optimization for Efficient and Reliable Reasoning

🔹 Publication Date: Published on Oct 26

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.22543
• PDF: https://arxiv.org/pdf/2510.22543
• Project Page: https://fapo-rl.github.io/
• Github: https://fapo-rl.github.io

🔹 Datasets citing this paper:
• https://huggingface.co/datasets/dyyyyyyyy/FAPO-Critic
• https://huggingface.co/datasets/dyyyyyyyy/FAPO-Reasoning-Dataset

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🔹 Title: Evolving Diagnostic Agents in a Virtual Clinical Environment

🔹 Publication Date: Published on Oct 28

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24654
• PDF: https://arxiv.org/pdf/2510.24654
• Project Page: https://arxiv.org/html/2510.24654v1
• Github: https://github.com/MAGIC-AI4Med/DiagGym

🔹 Datasets citing this paper:
• https://huggingface.co/datasets/Henrychur/DiagBench

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🔹 Title: ChronoPlay: A Framework for Modeling Dual Dynamics and Authenticity in Game RAG Benchmarks

🔹 Publication Date: Published on Oct 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18455
• PDF: https://arxiv.org/pdf/2510.18455
• Project Page: https://hly1998.github.io/ChronoPlay/
• Github: https://github.com/hly1998/ChronoPlay

🔹 Datasets citing this paper:
• https://huggingface.co/datasets/leoner24/ChronoPlay-QA

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🔹 Title: Gaperon: A Peppered English-French Generative Language Model Suite

🔹 Publication Date: Published on Oct 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.25771
• PDF: https://arxiv.org/pdf/2510.25771

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🔹 Title: ODesign: A World Model for Biomolecular Interaction Design

🔹 Publication Date: Published on Oct 25

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.22304
• PDF: https://arxiv.org/pdf/2510.22304
• Project Page: https://odesign.lglab.ac.cn/

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🔹 Title: The Principles of Diffusion Models

🔹 Publication Date: Published on Oct 24

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.21890
• PDF: https://arxiv.org/pdf/2510.21890

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🔹 Title: Fortytwo: Swarm Inference with Peer-Ranked Consensus

🔹 Publication Date: Published on Oct 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24801
• PDF: https://arxiv.org/pdf/2510.24801
• Project Page: https://fortytwo.network/

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🔹 Title: Reasoning Language Model Inference Serving Unveiled: An Empirical Study

🔹 Publication Date: Published on Oct 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18672
• PDF: https://arxiv.org/pdf/2510.18672

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🔹 Title: MC-SJD : Maximal Coupling Speculative Jacobi Decoding for Autoregressive Visual Generation Acceleration

🔹 Publication Date: Published on Oct 28

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24211
• PDF: https://arxiv.org/pdf/2510.24211

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🔹 Title: Generative View Stitching

🔹 Publication Date: Published on Oct 28

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24718
• PDF: https://arxiv.org/pdf/2510.24718
• Project Page: https://andrewsonga.github.io/gvs/
• Github: https://github.com/andrewsonga/generative_view_stitching

🔹 Datasets citing this paper:
• https://huggingface.co/datasets/ndsong/gvs_benchmark

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🔹 Title: GraphNet: A Large-Scale Computational Graph Dataset for Tensor Compiler Research

🔹 Publication Date: Published on Oct 28

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24035
• PDF: https://arxiv.org/pdf/2510.24035
• Github: https://github.com/PaddlePaddle/GraphNet

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🔹 Title: Automating Benchmark Design

🔹 Publication Date: Published on Oct 28

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.25039
• PDF: https://arxiv.org/pdf/2510.25039

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🤖🧠 Reflex: Build Full-Stack Web Apps in Pure Python — Fast, Flexible and Powerful

🗓️ 29 Oct 2025
📚 AI News & Trends

Building modern web applications has traditionally required mastering multiple languages and frameworks from JavaScript for the frontend to Python, Java or Node.js for the backend. For many developers, switching between different technologies can slow down productivity and increase complexity. Reflex eliminates that problem. It is an innovative open-source full-stack web framework that allows developers to ...

#Reflex #FullStack #WebDevelopment #Python #OpenSource #WebApps

🤖🧠 MLOps Basics: A Complete Guide to Building, Deploying and Monitoring Machine Learning Models

🗓️ 30 Oct 2025
📚 AI News & Trends

Machine Learning models are powerful but building them is only half the story. The true challenge lies in deploying, scaling and maintaining these models in production environments – a process that requires collaboration between data scientists, developers and operations teams. This is where MLOps (Machine Learning Operations) comes in. MLOps combines the principles of DevOps ...

#MLOps #MachineLearning #DevOps #ModelDeployment #DataScience #ProductionAI

🤖🧠 MiniMax-M2: The Open-Source Revolution Powering Coding and Agentic Intelligence

🗓️ 30 Oct 2025
📚 AI News & Trends

Artificial intelligence is evolving faster than ever, but not every innovation needs to be enormous to make an impact. MiniMax-M2, the latest release from MiniMax-AI, demonstrates that efficiency and power can coexist within a streamlined framework. MiniMax-M2 is an open-source Mixture of Experts (MoE) model designed for coding tasks, multi-agent collaboration and automation workflows. With ...

#MiniMaxM2 #OpenSource #MachineLearning #CodingAI #AgenticIntelligence #MixtureOfExperts

🔹 Title: The Quest for Reliable Metrics of Responsible AI

🔹 Publication Date: Published on Oct 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.26007
• PDF: https://arxiv.org/pdf/2510.26007

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🔹 Title: Kimi Linear: An Expressive, Efficient Attention Architecture

🔹 Publication Date: Published on Oct 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.26692
• PDF: https://arxiv.org/pdf/2510.26692
• Github: https://github.com/MoonshotAI/Kimi-Linear

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🔹 Title: Emu3.5: Native Multimodal Models are World Learners

🔹 Publication Date: Published on Oct 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.26583
• PDF: https://arxiv.org/pdf/2510.26583
• Project Page: https://emu.world/
• Github: https://github.com/baaivision/Emu3.5

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🔹 Title: Are Video Models Ready as Zero-Shot Reasoners? An Empirical Study with the MME-CoF Benchmark

🔹 Publication Date: Published on Oct 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.26802
• PDF: https://arxiv.org/pdf/2510.26802
• Github: https://video-cof.github.io/

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🔹 Title: Remote Labor Index: Measuring AI Automation of Remote Work

🔹 Publication Date: Published on Oct 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.26787
• PDF: https://arxiv.org/pdf/2510.26787

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