🔹 Title: PRISMM-Bench: A Benchmark of Peer-Review Grounded Multimodal Inconsistencies

🔹 Publication Date: Published on Oct 18

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.16505
• PDF: https://arxiv.org/pdf/2510.16505
• Github: https://github.com/da-luggas/prismm-bench

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🔹 Title: Extracting alignment data in open models

🔹 Publication Date: Published on Oct 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18554
• PDF: https://arxiv.org/pdf/2510.18554

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🔹 Title: PokeeResearch: Effective Deep Research via Reinforcement Learning from AI Feedback and Robust Reasoning Scaffold

🔹 Publication Date: Published on Oct 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.15862
• PDF: https://arxiv.org/pdf/2510.15862
• Github: https://github.com/Pokee-AI/PokeeResearchOSS

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🔹 Title: Is Multilingual LLM Watermarking Truly Multilingual? A Simple Back-Translation Solution

🔹 Publication Date: Published on Oct 20

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18019
• PDF: https://arxiv.org/pdf/2510.18019
• Github: https://github.com/asimzz/steam

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🤖🧠 Mastering Large Language Models: Top #1 Complete Guide to Maxime Labonne’s LLM Course

🗓️ 22 Oct 2025
📚 AI News & Trends

In the rapidly evolving landscape of artificial intelligence, large language models (LLMs) have become the foundation of modern AI innovation powering tools like ChatGPT, Claude, Gemini and countless enterprise AI applications. However, building, fine-tuning and deploying these models require deep technical understanding and hands-on expertise. To bridge this knowledge gap, Maxime Labonne, a leading AI ...

#LLM #ArtificialIntelligence #MachineLearning #DeepLearning #AIEngineering #LargeLanguageModels

🔹 Title: GAS: Improving Discretization of Diffusion ODEs via Generalized Adversarial Solver

🔹 Publication Date: Published on Oct 20

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.17699
• PDF: https://arxiv.org/pdf/2510.17699
• Github: https://github.com/3145tttt/GAS

🔹 Datasets citing this paper:
• https://huggingface.co/datasets/bayes-group-diffusion/GAS-teachers

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🤖🧠 Enhancing AI Agent Capabilities with Glean Agent Toolkit: A Complete Guide for Developers

🗓️ 22 Oct 2025
📚 AI News & Trends

The evolution of AI agents has transformed how businesses manage knowledge, automate workflows and deliver intelligent support. However, one major challenge remains how to effectively connect these AI agents to enterprise data and productivity tools. This is where the Glean Agent Toolkit steps in. Developed by Glean, a leader in enterprise knowledge discovery, this open-source ...

#AIAgents #GleanAgentToolkit #EnterpriseAI #ArtificialIntelligence #DeveloperTools #KnowledgeDiscovery

🔹 Title: Think with 3D: Geometric Imagination Grounded Spatial Reasoning from Limited Views

🔹 Publication Date: Published on Oct 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18632
• PDF: https://arxiv.org/pdf/2510.18632

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🤖🧠 The Ultimate #1 Collection of AI Books In Awesome-AI-Books Repository

🗓️ 22 Oct 2025
📚 AI News & Trends

Artificial Intelligence (AI) has emerged as one of the most transformative technologies of the 21st century. From powering self-driving cars to enabling advanced conversational AI like ChatGPT, AI is redefining how humans interact with machines. However, mastering AI requires a strong foundation in theory, mathematics, programming and hands-on experimentation. For enthusiasts, students and professionals seeking ...

#ArtificialIntelligence #AIBooks #MachineLearning #DeepLearning #AIResources #TechBooks

🤖🧠 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