🔹 Title: UltraGen: High-Resolution Video Generation with Hierarchical Attention

🔹 Publication Date: Published on Oct 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18775
• PDF: https://arxiv.org/pdf/2510.18775
• Project Page: https://sjtuplayer.github.io/projects/UltraGen/

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🔹 Title: UniGenBench++: A Unified Semantic Evaluation Benchmark for Text-to-Image Generation

🔹 Publication Date: Published on Oct 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18701
• PDF: https://arxiv.org/pdf/2510.18701
• Project Page: https://codegoat24.github.io/UniGenBench/
• Github: https://github.com/CodeGoat24/UniGenBench

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🔹 Title: LightMem: Lightweight and Efficient Memory-Augmented Generation

🔹 Publication Date: Published on Oct 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18866
• PDF: https://arxiv.org/pdf/2510.18866
• Github: https://github.com/zjunlp/LightMem

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🔹 Title: Towards Faithful and Controllable Personalization via Critique-Post-Edit Reinforcement Learning

🔹 Publication Date: Published on Oct 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18849
• PDF: https://arxiv.org/pdf/2510.18849

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🔹 Title: ProCLIP: Progressive Vision-Language Alignment via LLM-based Embedder

🔹 Publication Date: Published on Oct 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18795
• PDF: https://arxiv.org/pdf/2510.18795

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🔹 Title: World-in-World: World Models in a Closed-Loop World

🔹 Publication Date: Published on Oct 20

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18135
• PDF: https://arxiv.org/pdf/2510.18135

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🔹 Title: MUG-V 10B: High-efficiency Training Pipeline for Large Video Generation Models

🔹 Publication Date: Published on Oct 20

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.17519
• PDF: https://arxiv.org/pdf/2510.17519
• Project Page: https://github.com/Shopee-MUG/MUG-V
• Github: https://github.com/Shopee-MUG/MUG-V

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🔹 Title: Video Reasoning without Training

🔹 Publication Date: Published on Oct 19

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.17045
• PDF: https://arxiv.org/pdf/2510.17045

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🔹 Title: ssToken: Self-modulated and Semantic-aware Token Selection for LLM Fine-tuning

🔹 Publication Date: Published on Oct 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18250
• PDF: https://arxiv.org/pdf/2510.18250

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🔹 Title: DSI-Bench: A Benchmark for Dynamic Spatial Intelligence

🔹 Publication Date: Published on Oct 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18873
• PDF: https://arxiv.org/pdf/2510.18873
• Project Page: https://dsibench.github.io/
• Github: https://github.com/SpatialVision/dsibench

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🔹 Title: Unleashing Scientific Reasoning for Bio-experimental Protocol Generation via Structured Component-based Reward Mechanism

🔹 Publication Date: Published on Oct 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.15600
• PDF: https://arxiv.org/pdf/2510.15600

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🔹 Title: Mono4DGS-HDR: High Dynamic Range 4D Gaussian Splatting from Alternating-exposure Monocular Videos

🔹 Publication Date: Published on Oct 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18489
• PDF: https://arxiv.org/pdf/2510.18489
• Project Page: https://liujf1226.github.io/Mono4DGS-HDR/
• Github: https://github.com/LiuJF1226/Mono4DGS-HDR

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🔹 Title: EvoSyn: Generalizable Evolutionary Data Synthesis for Verifiable Learning

🔹 Publication Date: Published on Oct 20

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.17928
• PDF: https://arxiv.org/pdf/2510.17928
• Github: https://github.com/kinza99/openevolve

🔹 Datasets citing this paper:
• https://huggingface.co/datasets/Elynden/AgentBench-EvoSyn
• https://huggingface.co/datasets/Elynden/LiveCodeBench-EvoSyn

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🔹 Title: AlphaQuanter: An End-to-End Tool-Orchestrated Agentic Reinforcement Learning Framework for Stock Trading

🔹 Publication Date: Published on Oct 16

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.14264
• PDF: https://arxiv.org/pdf/2510.14264
• Project Page: https://alphaquanter.github.io/
• Github: https://github.com/AlphaQuanter/AlphaQuanter

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🔹 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