🔹 Title: AlphaFlow: Understanding and Improving MeanFlow Models

🔹 Publication Date: Published on Oct 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.20771
• PDF: https://arxiv.org/pdf/2510.20771
• Github: https://github.com/snap-research/alphaflow

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🔹 Title: Open-o3 Video: Grounded Video Reasoning with Explicit Spatio-Temporal Evidence

🔹 Publication Date: Published on Oct 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.20579
• PDF: https://arxiv.org/pdf/2510.20579
• Project Page: https://marinero4972.github.io/projects/Open-o3-Video/

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🔹 Title: Loopholing Discrete Diffusion: Deterministic Bypass of the Sampling Wall

🔹 Publication Date: Published on Oct 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.19304
• PDF: https://arxiv.org/pdf/2510.19304

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🔹 Title: ImpossibleBench: Measuring LLMs' Propensity of Exploiting Test Cases

🔹 Publication Date: Published on Oct 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.20270
• PDF: https://arxiv.org/pdf/2510.20270

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🔹 Title: ARGenSeg: Image Segmentation with Autoregressive Image Generation Model

🔹 Publication Date: Published on Oct 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.20803
• PDF: https://arxiv.org/pdf/2510.20803

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🔹 Title: Human-Agent Collaborative Paper-to-Page Crafting for Under $0.1

🔹 Publication Date: Published on Oct 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.19600
• PDF: https://arxiv.org/pdf/2510.19600
• Project Page: https://mqleet.github.io/AutoPage_ProjectPage
• Github: https://github.com/AutoLab-SAI-SJTU/AutoPage

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🔹 Title: Conan: Progressive Learning to Reason Like a Detective over Multi-Scale Visual Evidence

🔹 Publication Date: Published on Oct 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.20470
• PDF: https://arxiv.org/pdf/2510.20470
• Github: https://github.com/OuyangKun10/Conan

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🔹 Title: AdaSPEC: Selective Knowledge Distillation for Efficient Speculative Decoders

🔹 Publication Date: Published on Oct 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.19779
• PDF: https://arxiv.org/pdf/2510.19779
• Github: https://github.com/yuezhouhu/adaspec

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🔹 Title: The Massive Legal Embedding Benchmark (MLEB)

🔹 Publication Date: Published on Oct 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.19365
• PDF: https://arxiv.org/pdf/2510.19365
• Project Page: https://isaacus.com/mleb
• Github: https://github.com/isaacus-dev/mleb

🔹 Datasets citing this paper:
• https://huggingface.co/datasets/isaacus/mteb-barexam-qa
• https://huggingface.co/datasets/isaacus/mleb-scalr
• https://huggingface.co/datasets/isaacus/australian-tax-guidance-retrieval
• https://huggingface.co/datasets/isaacus/gdpr-holdings-retrieval

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🔹 Title: DyPE: Dynamic Position Extrapolation for Ultra High Resolution Diffusion

🔹 Publication Date: Published on Oct 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.20766
• PDF: https://arxiv.org/pdf/2510.20766
• Project Page: https://noamissachar.github.io/DyPE/
• Github: https://github.com/guyyariv/DyPE

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🔹 Title: Search Self-play: Pushing the Frontier of Agent Capability without Supervision

🔹 Publication Date: Published on Oct 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18821
• PDF: https://arxiv.org/pdf/2510.18821
• Github: https://github.com/Alibaba-Quark/SSP

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🔹 Title: From Masks to Worlds: A Hitchhiker's Guide to World Models

🔹 Publication Date: Published on Oct 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.20668
• PDF: https://arxiv.org/pdf/2510.20668
• Github: https://github.com/M-E-AGI-Lab/Awesome-World-Models

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🔹 Title: Emergence of Linear Truth Encodings in Language Models

🔹 Publication Date: Published on Oct 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.15804
• PDF: https://arxiv.org/pdf/2510.15804

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🔹 Title: Seed3D 1.0: From Images to High-Fidelity Simulation-Ready 3D Assets

🔹 Publication Date: Published on Oct 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.19944
• PDF: https://arxiv.org/pdf/2510.19944
• Project Page: https://seed.bytedance.com/seed3d

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🔹 Title: Thought Communication in Multiagent Collaboration

🔹 Publication Date: Published on Oct 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.20733
• PDF: https://arxiv.org/pdf/2510.20733

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🔹 Title: SAKE: Towards Editing Auditory Attribute Knowledge of Large Audio-Language Models

🔹 Publication Date: Published on Oct 19

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.16917
• PDF: https://arxiv.org/pdf/2510.16917
• Project Page: https://github.com/ckyang1124/SAKE
• Github: https://github.com/ckyang1124/SAKE

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🔹 Title: Investigating Safety Vulnerabilities of Large Audio-Language Models Under Speaker Emotional Variations

🔹 Publication Date: Published on Oct 19

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.16893
• PDF: https://arxiv.org/pdf/2510.16893
• Project Page: https://github.com/WoZhenDeShenMeDouBuZhidao/LALM-emotional-vulnerability
• Github: https://github.com/WoZhenDeShenMeDouBuZhidao/LALM-emotional-vulnerability

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🔹 Title: Diff-XYZ: A Benchmark for Evaluating Diff Understanding

🔹 Publication Date: Published on Oct 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.12487
• PDF: https://arxiv.org/pdf/2510.12487

🔹 Datasets citing this paper:
• https://huggingface.co/datasets/JetBrains-Research/diff-xyz

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🔹 Title: ComProScanner: A multi-agent based framework for composition-property structured data extraction from scientific literature

🔹 Publication Date: Published on Oct 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.20362
• PDF: https://arxiv.org/pdf/2510.20362

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🔹 Title: Communication to Completion: Modeling Collaborative Workflows with Intelligent Multi-Agent Communication

🔹 Publication Date: Published on Oct 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.19995
• PDF: https://arxiv.org/pdf/2510.19995

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🤖🧠 LangChain: The Ultimate Framework for Building Reliable AI Agents and LLM Applications

🗓️ 24 Oct 2025
📚 AI News & Trends

As artificial intelligence continues to transform industries, developers are racing to build smarter, more adaptive applications powered by Large Language Models (LLMs). Yet, one major challenge remains how to make these models interact intelligently with real-world data and external systems in a scalable, reliable way. Enter LangChain, an open-source framework designed to make LLM-powered application ...

#LangChain #AI #LLM #ArtificialIntelligence #OpenSource #AIAgents