🤖🧠 LandingAI ADE Python SDK: Streamlining AI-Powered Document Understanding

🗓️ 22 Oct 2025
📚 AI News & Trends

In the age of AI automation, extracting structured data from documents has become a key part of many business workflows. From invoices and contracts to identity documents and research papers, organizations are relying on AI models to interpret and process information accurately. LandingAI’s ADE Python SDK – an official API client for the LandingAI ADE ...

#AIPowered #DocumentUnderstanding #LandingAI #ADEPythonSDK #AIAutomation #DataExtraction

🔹 Title: Efficient Long-context Language Model Training by Core Attention Disaggregation

🔹 Publication Date: Published on Oct 20

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18121
• PDF: https://arxiv.org/pdf/2510.18121

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🔹 Title: Expanding the Action Space of LLMs to Reason Beyond Language

🔹 Publication Date: Published on Oct 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.07581
• PDF: https://arxiv.org/pdf/2510.07581
• Project Page: https://expa-rl.github.io/
• Github: https://github.com/yue-zhongqi/earl

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🔹 Title: Planned Diffusion

🔹 Publication Date: Published on Oct 20

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18087
• PDF: https://arxiv.org/pdf/2510.18087

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🔹 Title: Unimedvl: Unifying Medical Multimodal Understanding And Generation Through Observation-Knowledge-Analysis

🔹 Publication Date: Published on Oct 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.15710
• PDF: https://arxiv.org/pdf/2510.15710
• Project Page: https://uni-medical.github.io/UniMedVL_Web/
• Github: https://github.com/uni-medical/UniMedVL

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🔹 Title: Static Sandboxes Are Inadequate: Modeling Societal Complexity Requires Open-Ended Co-Evolution in LLM-Based Multi-Agent Simulations

🔹 Publication Date: Published on Oct 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.13982
• PDF: https://arxiv.org/pdf/2510.13982

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🔹 Title: Any-Depth Alignment: Unlocking Innate Safety Alignment of LLMs to Any-Depth

🔹 Publication Date: Published on Oct 20

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18081
• PDF: https://arxiv.org/pdf/2510.18081

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🔹 Title: Predicting the Unpredictable: Reproducible BiLSTM Forecasting of Incident Counts in the Global Terrorism Database (GTD)

🔹 Publication Date: Published on Oct 16

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.15136
• PDF: https://arxiv.org/pdf/2510.15136
• Github: https://github.com/Davidavid45/Deep-Learning-in-Counterterrorism

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🔹 Title: When "Correct" Is Not Safe: Can We Trust Functionally Correct Patches Generated by Code Agents?

🔹 Publication Date: Published on Oct 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.17862
• PDF: https://arxiv.org/pdf/2510.17862

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🔹 Title: Pruning Overparameterized Multi-Task Networks for Degraded Web Image Restoration

🔹 Publication Date: Published on Oct 16

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.14463
• PDF: https://arxiv.org/pdf/2510.14463
• Github: https://github.com/Thomkat/MIR-L

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🤖🧠 Unlocking Creativity with Awesome ChatGPT Prompts: The Ultimate Guide for AI Enthusiasts

🗓️ 22 Oct 2025
📚 AI News & Trends

Artificial Intelligence has transformed how we create, communicate, and innovate and at the heart of this revolution lies prompt engineering. One of the most powerful tools in this domain is the “Awesome ChatGPT Prompts” repository – a growing collection of creative, technical and professional prompts designed for ChatGPT and other large language models like Claude, ...

#ChatGPT #PromptEngineering #AIEnthusiasts #ArtificialIntelligence #LargeLanguageModels #AICreativity

🤖🧠 AgentFly: The Future of Reinforcement Learning for Intelligent Language Model Agents

🗓️ 22 Oct 2025
📚 AI News & Trends

AgentFly is a cutting-edge framework developed by researchers at the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) to revolutionize how large language models (LLMs) learn and act. It combines the power of reinforcement learning (RL) with language model agents enabling them to go beyond static prompt responses and learn through real-time feedback and experience. ...

#ReinforcementLearning #LLMs #LanguageModelAgents #ArtificialIntelligence #AgentFly #AIFramework

🤖🧠 OpenSearch for AI Agents: Empowering Intelligent Search and Automation

🗓️ 22 Oct 2025
📚 AI News & Trends

As artificial intelligence (AI) continues to evolve, one of the most transformative shifts has been the rise of AI agents – autonomous systems capable of reasoning, interacting, and performing complex tasks. From customer support chatbots to autonomous data analysts, these agents rely heavily on efficient data retrieval mechanisms. However, traditional search systems often struggle to ...

#OpenSearch #AIAgents #IntelligentSearch #AIautomation #ArtificialIntelligence #DataRetrieval

🔹 Title: LoongRL:Reinforcement Learning for Advanced Reasoning over Long Contexts

🔹 Publication Date: Published on Oct 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.19363
• PDF: https://arxiv.org/pdf/2510.19363

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🔹 Title: DaMo: Data Mixing Optimizer in Fine-tuning Multimodal LLMs for Mobile Phone Agents

🔹 Publication Date: Published on Oct 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.19336
• PDF: https://arxiv.org/pdf/2510.19336

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🔹 Title: olmOCR 2: Unit Test Rewards for Document OCR

🔹 Publication Date: Published on Oct 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.19817
• PDF: https://arxiv.org/pdf/2510.19817
• Project Page: https://olmocr.allen.ai/
• Github: https://github.com/allenai/olmocr

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🔹 Title: Pico-Banana-400K: A Large-Scale Dataset for Text-Guided Image Editing

🔹 Publication Date: Published on Oct 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.19808
• PDF: https://arxiv.org/pdf/2510.19808

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🔹 Title: VideoAgentTrek: Computer Use Pretraining from Unlabeled Videos

🔹 Publication Date: Published on Oct 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.19488
• PDF: https://arxiv.org/pdf/2510.19488
• Project Page: https://videoagenttrek.github.io/
• Github: https://github.com/xlang-ai/VideoAgentTrek

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🔹 Title: TheMCPCompany: Creating General-purpose Agents with Task-specific Tools

🔹 Publication Date: Published on Oct 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.19286
• PDF: https://arxiv.org/pdf/2510.19286
• Github: https://github.com/Reza-esfandiarpoor/the-mcp-company

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🔹 Title: Every Attention Matters: An Efficient Hybrid Architecture for Long-Context Reasoning

🔹 Publication Date: Published on Oct 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.19338
• PDF: https://arxiv.org/pdf/2510.19338

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🔹 Title: ColorAgent: Building A Robust, Personalized, and Interactive OS Agent

🔹 Publication Date: Published on Oct 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.19386
• PDF: https://arxiv.org/pdf/2510.19386
• Github: https://github.com/MadeAgents/mobile-use

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