ML Research Hub – Telegram
ML Research Hub
32.8K subscribers
4.21K photos
253 videos
23 files
4.54K links
Advancing research in Machine Learning – practical insights, tools, and techniques for researchers.

Admin: @HusseinSheikho || @Hussein_Sheikho
Download Telegram
🤖🧠 Master Machine Learning: Explore the Ultimate “Machine-Learning-Tutorials” Repository

🗓️ 23 Oct 2025
📚 AI News & Trends

In today’s data-driven world, Machine Learning (ML) has become the cornerstone of modern technology from intelligent chatbots to predictive analytics and recommendation systems. However, mastering ML isn’t just about coding, it requires a structured understanding of algorithms, statistics, optimization techniques and real-world problem-solving. That’s where Ujjwal Karn’s Machine-Learning-Tutorials GitHub repository stands out. This open-source, topic-wise ...

#MachineLearning #MLTutorials #ArtificialIntelligence #DataScience #OpenSource #AIEducation
🔹 Title: What Questions Should Robots Be Able to Answer? A Dataset of User Questions for Explainable Robotics

🔹 Publication Date: Published on Oct 18

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.16435
• PDF: https://arxiv.org/pdf/2510.16435

🔹 Datasets citing this paper:
https://huggingface.co/datasets/lwachowiak/xai-questions-dataset

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

For more data science resources:
https://news.1rj.ru/str/DataScienceT
🔹 Title: Steering Autoregressive Music Generation with Recursive Feature Machines

🔹 Publication Date: Published on Oct 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.19127
• PDF: https://arxiv.org/pdf/2510.19127
• Github: https://github.com/astradzhao/music-rfm

🔹 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: SAVANT: Semantic Analysis with Vision-Augmented Anomaly deTection

🔹 Publication Date: Published on Oct 20

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18034
• PDF: https://arxiv.org/pdf/2510.18034

🔹 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: Accelerating Vision Transformers with Adaptive Patch Sizes

🔹 Publication Date: Published on Oct 20

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18091
• PDF: https://arxiv.org/pdf/2510.18091
• Github: https://github.com/rccchoudhury/apt

🔹 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: Text or Pixels? It Takes Half: On the Token Efficiency of Visual Text Inputs in Multimodal LLMs

🔹 Publication Date: Published on Oct 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18279
• PDF: https://arxiv.org/pdf/2510.18279
• Github: https://github.com/yanhong-lbh/text_or_pixels

🔹 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: Every Question Has Its Own Value: Reinforcement Learning with Explicit Human Values

🔹 Publication Date: Published on Oct 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.20187
• PDF: https://arxiv.org/pdf/2510.20187

🔹 Datasets citing this paper:
https://huggingface.co/datasets/sarosavo/RLEV

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

For more data science resources:
https://news.1rj.ru/str/DataScienceT
🔹 Title: HoloCine: Holistic Generation of Cinematic Multi-Shot Long Video Narratives

🔹 Publication Date: Published on Oct 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.20822
• PDF: https://arxiv.org/pdf/2510.20822
• Project Page: https://holo-cine.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: LayerComposer: Interactive Personalized T2I via Spatially-Aware Layered Canvas

🔹 Publication Date: Published on Oct 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.20820
• PDF: https://arxiv.org/pdf/2510.20820
• Project Page: https://snap-research.github.io/layercomposer/

🔹 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: AlphaFlow: Understanding and Improving MeanFlow Models

🔹 Publication Date: Published on Oct 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.20771
• PDF: https://arxiv.org/pdf/2510.20771
• Github: https://github.com/snap-research/alphaflow

🔹 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: Open-o3 Video: Grounded Video Reasoning with Explicit Spatio-Temporal Evidence

🔹 Publication Date: Published on Oct 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.20579
• PDF: https://arxiv.org/pdf/2510.20579
• Project Page: https://marinero4972.github.io/projects/Open-o3-Video/

🔹 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: Loopholing Discrete Diffusion: Deterministic Bypass of the Sampling Wall

🔹 Publication Date: Published on Oct 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.19304
• PDF: https://arxiv.org/pdf/2510.19304

🔹 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: ImpossibleBench: Measuring LLMs' Propensity of Exploiting Test Cases

🔹 Publication Date: Published on Oct 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.20270
• PDF: https://arxiv.org/pdf/2510.20270

🔹 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: ARGenSeg: Image Segmentation with Autoregressive Image Generation Model

🔹 Publication Date: Published on Oct 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.20803
• PDF: https://arxiv.org/pdf/2510.20803

🔹 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: Human-Agent Collaborative Paper-to-Page Crafting for Under $0.1

🔹 Publication Date: Published on Oct 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.19600
• PDF: https://arxiv.org/pdf/2510.19600
• Project Page: https://mqleet.github.io/AutoPage_ProjectPage
• Github: https://github.com/AutoLab-SAI-SJTU/AutoPage

🔹 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: Conan: Progressive Learning to Reason Like a Detective over Multi-Scale Visual Evidence

🔹 Publication Date: Published on Oct 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.20470
• PDF: https://arxiv.org/pdf/2510.20470
• Github: https://github.com/OuyangKun10/Conan

🔹 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: AdaSPEC: Selective Knowledge Distillation for Efficient Speculative Decoders

🔹 Publication Date: Published on Oct 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.19779
• PDF: https://arxiv.org/pdf/2510.19779
• Github: https://github.com/yuezhouhu/adaspec

🔹 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: The Massive Legal Embedding Benchmark (MLEB)

🔹 Publication Date: Published on Oct 22

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.19365
• PDF: https://arxiv.org/pdf/2510.19365
• Project Page: https://isaacus.com/mleb
• Github: https://github.com/isaacus-dev/mleb

🔹 Datasets citing this paper:
https://huggingface.co/datasets/isaacus/mteb-barexam-qa
https://huggingface.co/datasets/isaacus/mleb-scalr
https://huggingface.co/datasets/isaacus/australian-tax-guidance-retrieval
https://huggingface.co/datasets/isaacus/gdpr-holdings-retrieval

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

For more data science resources:
https://news.1rj.ru/str/DataScienceT
🔹 Title: DyPE: Dynamic Position Extrapolation for Ultra High Resolution Diffusion

🔹 Publication Date: Published on Oct 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.20766
• PDF: https://arxiv.org/pdf/2510.20766
• Project Page: https://noamissachar.github.io/DyPE/
• Github: https://github.com/guyyariv/DyPE

🔹 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 Self-play: Pushing the Frontier of Agent Capability without Supervision

🔹 Publication Date: Published on Oct 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18821
• PDF: https://arxiv.org/pdf/2510.18821
• Github: https://github.com/Alibaba-Quark/SSP

🔹 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: From Masks to Worlds: A Hitchhiker's Guide to World Models

🔹 Publication Date: Published on Oct 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.20668
• PDF: https://arxiv.org/pdf/2510.20668
• Github: https://github.com/M-E-AGI-Lab/Awesome-World-Models

🔹 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