🔹 Title: CoMAS: Co-Evolving Multi-Agent Systems via Interaction Rewards

🔹 Publication Date: Published on Oct 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.08529
• PDF: https://arxiv.org/pdf/2510.08529
• Github: https://github.com/xxyQwQ/CoMAS

🔹 Datasets citing this paper:
No datasets found

🔹 Spaces citing this paper:
No spaces found
==================================

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

🔹 Title: Learning on the Job: An Experience-Driven Self-Evolving Agent for Long-Horizon Tasks

🔹 Publication Date: Published on Oct 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.08002
• PDF: https://arxiv.org/pdf/2510.08002

🔹 Datasets citing this paper:
No datasets found

🔹 Spaces citing this paper:
No spaces found
==================================

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

🔹 Title: Memory Retrieval and Consolidation in Large Language Models through Function Tokens

🔹 Publication Date: Published on Oct 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.08203
• PDF: https://arxiv.org/pdf/2510.08203

🔹 Datasets citing this paper:
No datasets found

🔹 Spaces citing this paper:
No spaces found
==================================

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

🔹 Title: Fidelity-Aware Data Composition for Robust Robot Generalization

🔹 Publication Date: Published on Sep 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.24797
• PDF: https://arxiv.org/pdf/2509.24797

🔹 Datasets citing this paper:
No datasets found

🔹 Spaces citing this paper:
No spaces found
==================================

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

🔹 Title: Beyond Outliers: A Study of Optimizers Under Quantization

🔹 Publication Date: Published on Sep 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.23500
• PDF: https://arxiv.org/pdf/2509.23500

🔹 Datasets citing this paper:
No datasets found

🔹 Spaces citing this paper:
No spaces found
==================================

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

🔹 Title: Taming Text-to-Sounding Video Generation via Advanced Modality Condition and Interaction

🔹 Publication Date: Published on Oct 3

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.03117
• PDF: https://arxiv.org/pdf/2510.03117
• Project Page: https://bridgedit-t2sv.github.io/

🔹 Datasets citing this paper:
No datasets found

🔹 Spaces citing this paper:
No spaces found
==================================

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

🔹 Title: Search-R3: Unifying Reasoning and Embedding Generation in Large Language Models

🔹 Publication Date: Published on Oct 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.07048
• PDF: https://arxiv.org/pdf/2510.07048
• Github: https://github.com/ytgui/Search-R3

🔹 Datasets citing this paper:
No datasets found

🔹 Spaces citing this paper:
No spaces found
==================================

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

🔹 Title: GCPO: When Contrast Fails, Go Gold

🔹 Publication Date: Published on Oct 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.07790
• PDF: https://arxiv.org/pdf/2510.07790
• Github: https://github.com/AchoWu/GCPO

🔹 Datasets citing this paper:
No datasets found

🔹 Spaces citing this paper:
No spaces found
==================================

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

🔹 Title: SViM3D: Stable Video Material Diffusion for Single Image 3D Generation

🔹 Publication Date: Published on Oct 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.08271
• PDF: https://arxiv.org/pdf/2510.08271

🔹 Datasets citing this paper:
No datasets found

🔹 Spaces citing this paper:
No spaces found
==================================

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

🔹 Title: GyroSwin: 5D Surrogates for Gyrokinetic Plasma Turbulence Simulations

🔹 Publication Date: Published on Oct 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.07314
• PDF: https://arxiv.org/pdf/2510.07314

🔹 Datasets citing this paper:
No datasets found

🔹 Spaces citing this paper:
No spaces found
==================================

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

🔹 Title: Drive&Gen: Co-Evaluating End-to-End Driving and Video Generation Models

🔹 Publication Date: Published on Oct 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.06209
• PDF: https://arxiv.org/pdf/2510.06209

🔹 Datasets citing this paper:
No datasets found

🔹 Spaces citing this paper:
No spaces found
==================================

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

🔹 Title: OmniRetarget: Interaction-Preserving Data Generation for Humanoid Whole-Body Loco-Manipulation and Scene Interaction

🔹 Publication Date: Published on Sep 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.26633
• PDF: https://arxiv.org/pdf/2509.26633
• Project Page: https://omniretarget.github.io/

🔹 Datasets citing this paper:
No datasets found

🔹 Spaces citing this paper:
No spaces found
==================================

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

🔹 Title: DreamOmni2: Multimodal Instruction-based Editing and Generation

🔹 Publication Date: Published on Oct 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.06679
• PDF: https://arxiv.org/pdf/2510.06679
• Project Page: https://pbihao.github.io/projects/DreamOmni2/index.html
• Github: https://github.com/dvlab-research/DreamOmni2

🔹 Datasets citing this paper:
No datasets found

🔹 Spaces citing this paper:
No spaces found
==================================

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

🔹 Title: Use the Online Network If You Can: Towards Fast and Stable Reinforcement Learning

🔹 Publication Date: Published on Oct 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.02590
• PDF: https://arxiv.org/pdf/2510.02590

🔹 Datasets citing this paper:
No datasets found

🔹 Spaces citing this paper:
No spaces found
==================================

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

🔹 Title: OpenRubrics: Towards Scalable Synthetic Rubric Generation for Reward Modeling and LLM Alignment

🔹 Publication Date: Published on Oct 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.07743
• PDF: https://arxiv.org/pdf/2510.07743

🔹 Datasets citing this paper:
No datasets found

🔹 Spaces citing this paper:
No spaces found
==================================

For more data science resources:
✓ https://news.1rj.ru/str/DataScienceT

🤖🧠 Join the 5-Day AI Agents Intensive Course with Google

🗓️ 07 Oct 2025
📚 AI News & Trends

Artificial Intelligence is rapidly evolving beyond chatbots and text generation. The next frontier is AI agents — intelligent, autonomous systems that can reason, take action and collaborate with tools and other agents. To help developers and practitioners build these next-generation systems, Google is launching the 5-Day AI Agents Intensive, a no-cost, online program running from ...

#aiagents #dayai #googleartificial #agentsintelligent #ai #evolvingchatbots

🤖🧠 Cognee: Powerful Memory for AI Agents in Just 6 Lines of Code

🗓️ 07 Oct 2025
📚 AI News & Trends

Artificial Intelligence is evolving rapidly, but one of the biggest challenges for developers is building agents that remember, reason and adapt. Traditional RAG (Retrieval-Augmented Generation) systems often fall short when handling context, scalability and precision. That’s where Cognee comes in. It is an open-source framework designed to provide AI agents with memory using a unique ...

#AI #Memory #AIAgents #OpenSource #RAG #ArtificialIntelligence

🤖🧠 ROMA: The Ultimate AI Framework That Lets You Build High-Performance Agents in Minutes

🗓️ 11 Oct 2025
📚 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 ...

#AI #MachineLearning #MultiAgentSystems #ArtificialIntelligence #HighPerformance #ROMA

🤖🧠 15+ Gemini AI Photo Editing Prompts for Boys: Create Stunning Styles & Expressions in 2025

🗓️ 11 Oct 2025
📚 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 #PortraitPhotography #AIart #BoysFashion #2025Trends

🤖🧠 DeepEval: The Ultimate LLM Evaluation Framework for AI Developers

🗓️ 07 Oct 2025
📚 AI News & Trends

In today’s AI-driven world, large language models (LLMs) have become central to modern applications from chatbots to intelligent AI agents. However, ensuring the accuracy, reliability and safety of these models is a significant challenge. Even small errors, biases or hallucinations can result in misleading information, frustrated users or business setbacks. This is where DeepEval, an ...

#DeepEval #LLM #AIDevelopment #LanguageModels #ModelEvaluation #ArtificialIntelligence

🤖🧠 The Little Book of Deep Learning – A Complete Summary and Chapter-Wise Overview

🗓️ 08 Oct 2025
📚 AI News & Trends

In the ever-evolving world of Artificial Intelligence, deep learning continues to be the driving force behind breakthroughs in computer vision, speech recognition and natural language processing. For those seeking a clear, structured and accessible guide to understanding how deep learning really works, “The Little Book of Deep Learning” by François Fleuret is a gem. This ...

#DeepLearning #ArtificialIntelligence #MachineLearning #NeuralNetworks #AIGuides # FrancoisFleuret