🔹 Title: Code Aesthetics with Agentic Reward Feedback

🔹 Publication Date: Published on Oct 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.23272
• PDF: https://arxiv.org/pdf/2510.23272
• Project Page: https://bangx7.github.io/code-aesthetics/

🔹 Datasets citing this paper:
No datasets found

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

For more data science resources:
✓ https://t.me/DataScienceT

🔹 Title: Memory-based Language Models: An Efficient, Explainable, and Eco-friendly Approach to Large Language Modeling

🔹 Publication Date: Published on Oct 25

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.22317
• PDF: https://arxiv.org/pdf/2510.22317
• Github: https://github.com/antalvdb/olifant

🔹 Datasets citing this paper:
No datasets found

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

For more data science resources:
✓ https://t.me/DataScienceT

🔹 Title: Mitigating Attention Sinks and Massive Activations in Audio-Visual Speech Recognition with LLMS

🔹 Publication Date: Published on Oct 26

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.22603
• PDF: https://arxiv.org/pdf/2510.22603
• Github: https://github.com/umbertocappellazzo/Llama-AVSR

🔹 Datasets citing this paper:
No datasets found

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

For more data science resources:
✓ https://t.me/DataScienceT

🤖🧠 Free for 1 Year: ChatGPT Go’s Big Move in India

🗓️ 28 Oct 2025
📚 AI News & Trends

On 28 October 2025, OpenAI announced that its mid-tier subscription plan, ChatGPT Go, will be available free for one full year in India starting from 4 November. (www.ndtv.com) What is ChatGPT Go? What’s the deal? Why this matters ? Things to check / caveats What should users do? Broader implications This move by OpenAI indicates ...

#ChatGPTGo #OpenAI #India #FreeAccess #ArtificialIntelligence #TechNews

🔹 Title: The Best of N Worlds: Aligning Reinforcement Learning with Best-of-N Sampling via max@k Optimisation

🔹 Publication Date: Published on Oct 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.23393
• PDF: https://arxiv.org/pdf/2510.23393

🔹 Datasets citing this paper:
No datasets found

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

For more data science resources:
✓ https://t.me/DataScienceT

🔹 Title: EchoDistill: Bidirectional Concept Distillation for One-Step Diffusion Personalization

🔹 Publication Date: Published on Oct 23

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.20512
• PDF: https://arxiv.org/pdf/2510.20512

🔹 Datasets citing this paper:
No datasets found

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

For more data science resources:
✓ https://t.me/DataScienceT

🔹 Title: DiffusionLane: Diffusion Model for Lane Detection

🔹 Publication Date: Published on Oct 25

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.22236
• PDF: https://arxiv.org/pdf/2510.22236

🔹 Datasets citing this paper:
No datasets found

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

For more data science resources:
✓ https://t.me/DataScienceT

🔹 Title: Scaling Laws for Deepfake Detection

🔹 Publication Date: Published on Oct 18

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.16320
• PDF: https://arxiv.org/pdf/2510.16320

🔹 Datasets citing this paper:
No datasets found

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

For more data science resources:
✓ https://t.me/DataScienceT

🔹 Title: SyncHuman: Synchronizing 2D and 3D Generative Models for Single-view Human Reconstruction

🔹 Publication Date: Published on Oct 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.07723
• PDF: https://arxiv.org/pdf/2510.07723

🔹 Datasets citing this paper:
No datasets found

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

For more data science resources:
✓ https://t.me/DataScienceT

🔹 Title: Once Upon an Input: Reasoning via Per-Instance Program Synthesis

🔹 Publication Date: Published on Oct 26

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.22849
• PDF: https://arxiv.org/pdf/2510.22849
• Github: https://github.com/adaminsky/pips

🔹 Datasets citing this paper:
No datasets found

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

For more data science resources:
✓ https://t.me/DataScienceT

🔹 Title: Open Multimodal Retrieval-Augmented Factual Image Generation

🔹 Publication Date: Published on Oct 26

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.22521
• PDF: https://arxiv.org/pdf/2510.22521
• Project Page: https://tyangjn.github.io/orig.github.io/
• Github: https://github.com/TyangJN/ORIG

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

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

For more data science resources:
✓ https://t.me/DataScienceT

🔹 Title: FlowOpt: Fast Optimization Through Whole Flow Processes for Training-Free Editing

🔹 Publication Date: Published on Oct 24

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.22010
• PDF: https://arxiv.org/pdf/2510.22010
• Project Page: https://orronai.github.io/FlowOpt/
• Github: https://github.com/orronai/FlowOpt

🔹 Datasets citing this paper:
No datasets found

🔹 Spaces citing this paper:
• https://huggingface.co/spaces/orronai/FlowOpt
==================================

For more data science resources:
✓ https://t.me/DataScienceT

🤖🧠 Agent Lightning By Microsoft: Reinforcement Learning Framework to Train Any AI Agent

🗓️ 28 Oct 2025
📚 Agentic AI

Artificial Intelligence (AI) is rapidly moving from static models to intelligent agents capable of reasoning, adapting, and performing complex, real-world tasks. However, training these agents effectively remains a major challenge. Most frameworks today tightly couple the agent’s logic with training processes making it hard to scale or transfer across use cases. Enter Agent Lightning, a ...

#AgentLightning #Microsoft #ReinforcementLearning #AIAgents #ArtificialIntelligence #MachineLearning

🤖🧠 PandasAI: Transforming Data Analysis with Conversational Artificial Intelligence

🗓️ 28 Oct 2025
📚 AI News & Trends

In a world dominated by data, the ability to analyze and interpret information efficiently has become a core competitive advantage. From business intelligence dashboards to large-scale machine learning models, data-driven decision-making fuels innovation across industries. Yet, for most people, data analysis remains a technical challenge requiring coding expertise, statistical knowledge and familiarity with libraries like ...

#PandasAI #ConversationalAI #DataAnalysis #ArtificialIntelligence #DataScience #MachineLearning

🔹 Title: MergeMix: A Unified Augmentation Paradigm for Visual and Multi-Modal Understanding

🔹 Publication Date: Published on Oct 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.23479
• PDF: https://arxiv.org/pdf/2510.23479
• Github: https://github.com/Westlake-AI/openmixup

🔹 Datasets citing this paper:
No datasets found

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

For more data science resources:
✓ https://t.me/DataScienceT

🔹 Title: Multi-Agent Evolve: LLM Self-Improve through Co-evolution

🔹 Publication Date: Published on Oct 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.23595
• PDF: https://arxiv.org/pdf/2510.23595

🔹 Datasets citing this paper:
No datasets found

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

For more data science resources:
✓ https://t.me/DataScienceT

🔹 Title: Sprint: Sparse-Dense Residual Fusion for Efficient Diffusion Transformers

🔹 Publication Date: Published on Oct 24

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.21986
• PDF: https://arxiv.org/pdf/2510.21986

🔹 Datasets citing this paper:
No datasets found

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

For more data science resources:
✓ https://t.me/DataScienceT

🤖🧠 Microsoft Data Formulator: Revolutionizing AI-Powered Data Visualization

🗓️ 28 Oct 2025
📚 AI News & Trends

In today’s data-driven world, visualization is everything. Whether you’re a business analyst, data scientist or researcher, the ability to convert raw data into meaningful visuals can define the success of your decisions. That’s where Microsoft’s Data Formulator steps in a cutting-edge, open-source platform designed to empower analysts to create rich, AI-assisted visualizations effortlessly. Developed by ...

#Microsoft #DataVisualization #AI #DataScience #OpenSource #Analytics

🤖🧠 Google’s GenAI MCP Toolbox for Databases: Transforming AI-Powered Data Management

🗓️ 28 Oct 2025
📚 AI News & Trends

In the era of artificial intelligence, where data fuels innovation and decision-making, the need for efficient and intelligent data management tools has never been greater. Traditional methods of database management often require deep technical expertise and manual oversight, slowing down development cycles and creating operational bottlenecks. To address these challenges, Google has introduced the GenAI ...

#Google #GenAI #Database #AIPowered #DataManagement #MachineLearning

🤖🧠 Wren AI: Transforming Business Intelligence with Generative AI

🗓️ 28 Oct 2025
📚 AI News & Trends

In the evolving world of data and analytics, one thing is certain — the ability to transform raw data into actionable insights defines success. Organizations today are generating more data than ever before, yet accessing and understanding that data remains a significant challenge. Traditional business intelligence tools require technical expertise, SQL knowledge and manual configuration. ...

#WrenAI #GenerativeAI #BusinessIntelligence #DataAnalytics #AI #Insights

🔹 Title: VL-SAE: Interpreting and Enhancing Vision-Language Alignment with a Unified Concept Set

🔹 Publication Date: Published on Oct 24

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.21323
• PDF: https://arxiv.org/pdf/2510.21323
• Github: https://github.com/ssfgunner/VL-SAE

🔹 Datasets citing this paper:
No datasets found

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

For more data science resources:
✓ https://t.me/DataScienceT