ML Research Hub – Telegram
ML Research Hub
32.8K subscribers
4.32K photos
263 videos
23 files
4.67K links
Advancing research in Machine Learning – practical insights, tools, and techniques for researchers.

Admin: @HusseinSheikho || @Hussein_Sheikho
Download Telegram
🔹 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

🔹 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: 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

🔹 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: 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

🔹 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: 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

🔹 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: 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

🔹 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: 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

🔹 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: 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

🔹 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: 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

🔹 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: 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

🔹 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: 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

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

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

🔹 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
1
🔹 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

🔹 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: 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

🔹 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
1
🔹 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

🔹 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: 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

🔹 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
1
🤖🧠 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

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

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

🔹 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
🤖🧠 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