🤖🧠 Master Machine Learning with Stanford’s CS229 Cheatsheets: The Ultimate Learning Resource

🗓️ 21 Oct 2025
📚 AI News & Trends

Machine learning is one of the most transformative fields in technology today. From powering recommendation systems to enabling self-driving cars, machine learning is at the core of modern artificial intelligence. However, mastering its vast concepts, equations and algorithms can be overwhelming especially for beginners and busy professionals. That’s where the Stanford CS229 Machine Learning Cheatsheets ...

🔹 Title: TrajSelector: Harnessing Latent Representations for Efficient and Effective Best-of-N in Large Reasoning Model

🔹 Publication Date: Published on Oct 18

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.16449
• PDF: https://arxiv.org/pdf/2510.16449

🔹 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: AION-1: Omnimodal Foundation Model for Astronomical Sciences

🔹 Publication Date: Published on Oct 20

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.17960
• PDF: https://arxiv.org/pdf/2510.17960
• Github: https://github.com/PolymathicAI/AION

🔹 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: MoReBench: Evaluating Procedural and Pluralistic Moral Reasoning in Language Models, More than Outcomes

🔹 Publication Date: Published on Oct 18

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.16380
• PDF: https://arxiv.org/pdf/2510.16380
• Project Page: https://morebench.github.io/
• Github: https://github.com/morebench/morebench

🔹 Datasets citing this paper:
• https://huggingface.co/datasets/morebench/morebench

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

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

🔹 Title: Grasp Any Region: Towards Precise, Contextual Pixel Understanding for Multimodal LLMs

🔹 Publication Date: Published on Oct 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18876
• PDF: https://arxiv.org/pdf/2510.18876
• Github: https://github.com/Haochen-Wang409/Grasp-Any-Region

🔹 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 Step Evolves: Scaling Reinforcement Learning for Trillion-Scale Thinking Model

🔹 Publication Date: Published on Oct 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18855
• PDF: https://arxiv.org/pdf/2510.18855
• Github: https://github.com/inclusionAI/Ring-V2

🔹 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: IF-VidCap: Can Video Caption Models Follow Instructions?

🔹 Publication Date: Published on Oct 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18726
• PDF: https://arxiv.org/pdf/2510.18726
• Project Page: https://if-vidcap.github.io/
• Github: https://github.com/NJU-LINK/IF-VidCap

🔹 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: MoGA: Mixture-of-Groups Attention for End-to-End Long Video Generation

🔹 Publication Date: Published on Oct 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.18692
• PDF: https://arxiv.org/pdf/2510.18692

🔹 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: MT-Video-Bench: A Holistic Video Understanding Benchmark for Evaluating Multimodal LLMs in Multi-Turn Dialogues

🔹 Publication Date: Published on Oct 20

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.17722
• PDF: https://arxiv.org/pdf/2510.17722
• Project Page: https://mt-video-bench.github.io/
• Github: https://github.com/NJU-LINK/MT-Video-Bench

🔹 Datasets citing this paper:
• https://huggingface.co/datasets/NJU-LINK/MT-Video-Bench

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

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

🔹 Title: Chem-R: Learning to Reason as a Chemist

🔹 Publication Date: Published on Oct 19

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.16880
• PDF: https://arxiv.org/pdf/2510.16880
• Github: https://github.com/davidweidawang/Chem-R

🔹 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: 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/

🔹 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: 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

🔹 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: 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

🔹 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: 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