🔹 Title: LightBagel: A Light-weighted, Double Fusion Framework for Unified Multimodal Understanding and Generation

🔹 Publication Date: Published on Oct 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.22946
• PDF: https://arxiv.org/pdf/2510.22946
• Project Page: https://ucsc-vlaa.github.io/LightBagel/

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🔹 Title: LongCat-Video Technical Report

🔹 Publication Date: Published on Oct 25

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.22200
• PDF: https://arxiv.org/pdf/2510.22200
• Github: https://github.com/meituan-longcat/LongCat-Video

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🔹 Title: Lookahead Anchoring: Preserving Character Identity in Audio-Driven Human Animation

🔹 Publication Date: Published on Oct 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.23581
• PDF: https://arxiv.org/pdf/2510.23581
• Project Page: https://lookahead-anchoring.github.io/
• Github: https://lookahead-anchoring.github.io/

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🔹 Title: Track, Inpaint, Resplat: Subject-driven 3D and 4D Generation with Progressive Texture Infilling

🔹 Publication Date: Published on Oct 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.23605
• PDF: https://arxiv.org/pdf/2510.23605

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🔹 Title: VoMP: Predicting Volumetric Mechanical Property Fields

🔹 Publication Date: Published on Oct 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.22975
• PDF: https://arxiv.org/pdf/2510.22975
• Project Page: https://research.nvidia.com/labs/sil/projects/vomp

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🔹 Title: A Survey of Data Agents: Emerging Paradigm or Overstated Hype?

🔹 Publication Date: Published on Oct 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.23587
• PDF: https://arxiv.org/pdf/2510.23587
• Github: https://github.com/HKUSTDial/awesome-data-agents

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🔹 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/

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🔹 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

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🔹 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

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🤖🧠 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 subnoscription 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

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🔹 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

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🔹 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

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🔹 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

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🔹 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

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🔹 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

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🔹 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

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🔹 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

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🤖🧠 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

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