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Advancing research in Machine Learning – practical insights, tools, and techniques for researchers.

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πŸ€–πŸ§  ROMA: The Ultimate AI Framework That Lets You Build High-Performance Agents in Minutes

πŸ—“οΈ 11 Oct 2025
πŸ“š AI News & Trends

Artificial Intelligence continues to evolve at an unprecedented pace, with agent-based frameworks becoming increasingly important for tackling complex problems. ROMA (Recursive Open Meta-Agents) represents a significant leap forward in this space, providing developers and researchers with a hierarchical, flexible, and high-performance framework for building multi-agent AI systems. This article explores ROMA’s architecture, technical capabilities, practical ...

#ROMA #AIFramework #MultiAgentSystems #ArtificialIntelligence #HighPerformanceAI #AgentBasedAI
πŸ€–πŸ§  15+ Gemini AI Photo Editing Prompts for Boys: Create Stunning Styles & Expressions in 2025

πŸ—“οΈ 11 Oct 2025
πŸ“š AI News & Trends

Are you looking to take your portraits to the next level? With Gemini AI Photo Editing Prompts, boys can now turn ordinary photos into ultra-realistic, cinematic or high-fashion images effortlessly. These prompts are specifically designed to work with uploaded images, allowing you to enhance your existing photos while keeping the subject intact. Whether you’re curating ...

#GeminiAI #PhotoEditing #AIPrompts #PortraitPhotography #AIImageGeneration #BoysFashion
πŸ€–πŸ§  Artificial Intelligence: A Modern Approach β€” The Ultimate Number 1 Guide to Learning AI by Stuart Russell and Peter Norvig

πŸ—“οΈ 12 Oct 2025
πŸ“š AI News & Trends

When it comes to learning artificial intelligence (AI), few resources hold as much authority as β€œArtificial Intelligence: A Modern Approach” by Stuart Russell and Peter Norvig. Often regarded as the β€œBible of AI”, this textbook has become the most widely used academic reference in the field adopted by over 1,500 universities and institutions worldwide. Published ...

#ArtificialIntelligence #AIModernApproach #StuartRussell #PeterNorvig #AIBible #AIEducation
πŸ€–πŸ§  Grok AI Chatbot (2025): Elon Musk’s Bold Answer to Real-Time, Intelligent Conversation

πŸ—“οΈ 12 Oct 2025
πŸ“š AI News & Trends

The year 2025 marks a new era in the evolution of conversational AI and at the center of this transformation stands Grok AI, the innovative chatbot developed by Elon Musk’s company xAI. Grok isn’t just another virtual assistant; it’s a real-time intelligent system that combines deep reasoning with a unique, witty personality. What truly sets ...

#GrokAI #xAI #ConversationalAI #ElonMusk #RealTimeAI #IntelligentChatbot
πŸ”Ή Title: TAG:Tangential Amplifying Guidance for Hallucination-Resistant Diffusion Sampling

πŸ”Ή Publication Date: Published on Oct 6

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2510.04533
β€’ PDF: https://arxiv.org/pdf/2510.04533
β€’ Project Page: https://hyeon-cho.github.io/TAG/

πŸ”Ή Datasets citing this paper:
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πŸ”Ή Spaces citing this paper:
β€’ https://huggingface.co/spaces/hyeoncho01/Tangential-Amplifying-Guidance
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πŸ”Ή Title: ReviewerToo: Should AI Join The Program Committee? A Look At The Future of Peer Review

πŸ”Ή Publication Date: Published on Oct 9

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2510.08867
β€’ PDF: https://arxiv.org/pdf/2510.08867

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πŸ”Ή Title: Don't Waste Mistakes: Leveraging Negative RL-Groups via Confidence Reweighting

πŸ”Ή Publication Date: Published on Oct 9

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2510.08696
β€’ PDF: https://arxiv.org/pdf/2510.08696

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πŸ”Ή Title: StreamingVLM: Real-Time Understanding for Infinite Video Streams

πŸ”Ή Publication Date: Published on Oct 10

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2510.09608
β€’ PDF: https://arxiv.org/pdf/2510.09608
β€’ Github: https://github.com/mit-han-lab/streaming-vlm

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πŸ”Ή Title: SpaceVista: All-Scale Visual Spatial Reasoning from mm to km

πŸ”Ή Publication Date: Published on Oct 10

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2510.09606
β€’ PDF: https://arxiv.org/pdf/2510.09606
β€’ Project Page: https://peiwensun2000.github.io/mm2km/
β€’ Github: https://github.com/PeiwenSun2000/SpaceVista

πŸ”Ή Datasets citing this paper:
β€’ https://huggingface.co/datasets/SpaceVista/Data-Preview

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πŸ”Ή Title: Mind-Paced Speaking: A Dual-Brain Approach to Real-Time Reasoning in Spoken Language Models

πŸ”Ή Publication Date: Published on Oct 10

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2510.09592
β€’ PDF: https://arxiv.org/pdf/2510.09592
β€’ Github: https://github.com/stepfun-ai/Step-MPS

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πŸ”Ή Title: Dyna-Mind: Learning to Simulate from Experience for Better AI Agents

πŸ”Ή Publication Date: Published on Oct 10

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2510.09577
β€’ PDF: https://arxiv.org/pdf/2510.09577

πŸ”Ή Datasets citing this paper:
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πŸ”Ή Title: Pseudo2Real: Task Arithmetic for Pseudo-Label Correction in Automatic Speech Recognition

πŸ”Ή Publication Date: Published on Oct 9

πŸ”Ή Paper Links:
β€’ arXiv Page: https://www.arxiv.org/abs/2510.08047
β€’ PDF: https://arxiv.org/pdf/2510.08047

πŸ”Ή Datasets citing this paper:
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πŸ€–πŸ§  Try Powerful Mem0 AI to build Long-Term Memory for AI Agents

πŸ—“οΈ 12 Oct 2025
πŸ“š AI News & Trends

Artificial Intelligence has made incredible leaps in recent years from chatbots that converse naturally to AI agents capable of reasoning and decision-making. However, one major limitation has persisted: memory. Traditional large language models (LLMs) like ChatGPT or Claude can process vast data but fail to remember context across long interactions. This is where Mem0 AI, ...

#Mem0AI #AIAgents #LongTermMemory #ArtificialIntelligence #AIMemory #LLMs
πŸ”Ή Title: Thinking with Camera: A Unified Multimodal Model for Camera-Centric Understanding and Generation

πŸ”Ή Publication Date: Published on Oct 9

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2510.08673
β€’ PDF: https://arxiv.org/pdf/2510.08673
β€’ Project Page: https://kangliao929.github.io/projects/puffin/
β€’ Github: https://github.com/KangLiao929/Puffin

πŸ”Ή Datasets citing this paper:
β€’ https://huggingface.co/datasets/KangLiao/Puffin-4M

πŸ”Ή Spaces citing this paper:
β€’ https://huggingface.co/spaces/KangLiao/Puffin
β€’ https://huggingface.co/spaces/wusize/Puffin
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πŸ”Ή Title: Webscale-RL: Automated Data Pipeline for Scaling RL Data to Pretraining Levels

πŸ”Ή Publication Date: Published on Oct 7

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2510.06499
β€’ PDF: https://arxiv.org/pdf/2510.06499
β€’ Project Page: https://huggingface.co/datasets/Salesforce/Webscale-RL
β€’ Github: https://github.com/SalesforceAIResearch/PretrainRL-pipeline

πŸ”Ή Datasets citing this paper:
β€’ https://huggingface.co/datasets/Salesforce/Webscale-RL

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πŸ”Ή Title: Progressive Gaussian Transformer with Anisotropy-aware Sampling for Open Vocabulary Occupancy Prediction

πŸ”Ή Publication Date: Published on Oct 6

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2510.04759
β€’ PDF: https://arxiv.org/pdf/2510.04759
β€’ Project Page: https://yanchi-3dv.github.io/PG-Occ/
β€’ Github: https://github.com/yanchi-3dv/PG-Occ

πŸ”Ή Datasets citing this paper:
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πŸ”Ή Title: Multimodal Prompt Optimization: Why Not Leverage Multiple Modalities for MLLMs

πŸ”Ή Publication Date: Published on Oct 10

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2510.09201
β€’ PDF: https://arxiv.org/pdf/2510.09201
β€’ Github: https://github.com/Dozi01/MPO

πŸ”Ή Datasets citing this paper:
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πŸ”Ή Title: R-Horizon: How Far Can Your Large Reasoning Model Really Go in Breadth and Depth?

πŸ”Ή Publication Date: Published on Oct 9

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2510.08189
β€’ PDF: https://arxiv.org/pdf/2510.08189

πŸ”Ή Datasets citing this paper:
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πŸ”Ή Title: Parallel Test-Time Scaling for Latent Reasoning Models

πŸ”Ή Publication Date: Published on Oct 9

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2510.07745
β€’ PDF: https://arxiv.org/pdf/2510.07745
β€’ Github: https://github.com/YRYangang/LatentTTS

πŸ”Ή Datasets citing this paper:
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πŸ”Ή Title: TC-LoRA: Temporally Modulated Conditional LoRA for Adaptive Diffusion Control

πŸ”Ή Publication Date: Published on Oct 10

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2510.09561
β€’ PDF: https://arxiv.org/pdf/2510.09561

πŸ”Ή Datasets citing this paper:
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πŸ”Ή Title: PhysToolBench: Benchmarking Physical Tool Understanding for MLLMs

πŸ”Ή Publication Date: Published on Oct 10

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2510.09507
β€’ PDF: https://arxiv.org/pdf/2510.09507
β€’ Github: https://github.com/EnVision-Research/PhysToolBench

πŸ”Ή Datasets citing this paper:
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