🔹 Title: LiveResearchBench: A Live Benchmark for User-Centric Deep Research in the Wild

🔹 Publication Date: Published on Oct 16

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.14240
• PDF: https://arxiv.org/pdf/2510.14240

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🔹 Title: LLMs Can Get "Brain Rot"!

🔹 Publication Date: Published on Oct 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.13928
• PDF: https://arxiv.org/pdf/2510.13928

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🔹 Title: Predicting Task Performance with Context-aware Scaling Laws

🔹 Publication Date: Published on Oct 16

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.14919
• PDF: https://arxiv.org/pdf/2510.14919
• Github: https://github.com/wang-research-lab/context-scaling

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🔹 Title: Budget-aware Test-time Scaling via Discriminative Verification

🔹 Publication Date: Published on Oct 16

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.14913
• PDF: https://arxiv.org/pdf/2510.14913
• Github: https://github.com/wang-research-lab/verification

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🤖🧠 Sora: OpenAI’s Breakthrough Text-to-Video Model Transforming Visual Creativity

🗓️ 18 Oct 2025
📚 AI News & Trends

Introduction Artificial Intelligence (AI) is rapidly transforming the creative world. From generating realistic images to composing music and writing code, AI has redefined how humans interact with technology. But one of the most revolutionary advancements in this domain is Sora, OpenAI’s text-to-video generative model that converts written prompts into hyper-realistic video clips. Ithas captured global ...

#Sora #OpenAI #TextToVideo #AI #VisualCreativity #GenerativeModel

🤖🧠 Unleashing the Power of AI with Open Agent Builder: A Visual Workflow Tool for AI Agents

🗓️ 19 Oct 2025
📚 AI News & Trends

In today’s rapidly advancing technological landscape, artificial intelligence (AI) is not just a buzzword, it’s a transformative force across industries. From automating complex tasks to streamlining operations, AI is revolutionizing workflows. However, designing and deploying AI-driven workflows has traditionally required expert-level programming knowledge. Enter Open Agent Builder, a revolutionary tool that democratizes the creation of ...

#AI #ArtificialIntelligence #OpenAgentBuilder #AIAgents #VisualWorkflow #TechInnovation

🔹 Title: MorphoBench: A Benchmark with Difficulty Adaptive to Model Reasoning

🔹 Publication Date: Published on Oct 16

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.14265
• PDF: https://arxiv.org/pdf/2510.14265
• Github: https://github.com/OpenDCAI/MorphoBench

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🔹 Title: Skyfall-GS: Synthesizing Immersive 3D Urban Scenes from Satellite Imagery

🔹 Publication Date: Published on Oct 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.15869
• PDF: https://arxiv.org/pdf/2510.15869
• Project Page: https://skyfall-gs.jayinnn.dev/
• Github: https://github.com/jayin92/skyfall-gs

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🔹 Title: OmniVinci: Enhancing Architecture and Data for Omni-Modal Understanding LLM

🔹 Publication Date: Published on Oct 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.15870
• PDF: https://arxiv.org/pdf/2510.15870
• Project Page: https://nvlabs.github.io/OmniVinci/
• Github: https://github.com/NVlabs/OmniVinci

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🔹 Title: BLIP3o-NEXT: Next Frontier of Native Image Generation

🔹 Publication Date: Published on Oct 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.15857
• PDF: https://arxiv.org/pdf/2510.15857
• Project Page: https://jiuhaichen.github.io/BLIP3o-NEXT.github.io/

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🔹 Title: Imaginarium: Vision-guided High-Quality 3D Scene Layout Generation

🔹 Publication Date: Published on Oct 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.15564
• PDF: https://arxiv.org/pdf/2510.15564
• Github: https://github.com/HiHiAllen/Imaginarium

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🔹 Title: Explore to Evolve: Scaling Evolved Aggregation Logic via Proactive Online Exploration for Deep Research Agents

🔹 Publication Date: Published on Oct 16

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.14438
• PDF: https://arxiv.org/pdf/2510.14438
• Github: https://github.com/Tencent/WebAggregator

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

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🔹 Title: Paper2Web: Let's Make Your Paper Alive!

🔹 Publication Date: Published on Oct 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.15842
• PDF: https://arxiv.org/pdf/2510.15842
• Project Page: https://francischen3.github.io/P2W_Website/
• Github: https://github.com/YuhangChen1/Paper2All

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🔹 Title: Scaling Instruction-Based Video Editing with a High-Quality Synthetic Dataset

🔹 Publication Date: Published on Oct 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.15742
• PDF: https://arxiv.org/pdf/2510.15742
• Project Page: https://ezioby.github.io/Ditto_page
• Github: https://github.com/EzioBy/Ditto

🔹 Datasets citing this paper:
• https://huggingface.co/datasets/QingyanBai/Ditto-1M

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🔹 Title: Latent Diffusion Model without Variational Autoencoder

🔹 Publication Date: Published on Oct 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.15301
• PDF: https://arxiv.org/pdf/2510.15301
• Project Page: https://howlin-wang.github.io/svg/
• Github: https://github.com/shiml20/SVG

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🔹 Title: FinTrust: A Comprehensive Benchmark of Trustworthiness Evaluation in Finance Domain

🔹 Publication Date: Published on Oct 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.15232
• PDF: https://arxiv.org/pdf/2510.15232
• Github: https://github.com/HughieHu/FinTrust/

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

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🔹 Title: VISTA: A Test-Time Self-Improving Video Generation Agent

🔹 Publication Date: Published on Oct 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.15831
• PDF: https://arxiv.org/pdf/2510.15831
• Github: https://g-vista.github.io/

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🔹 Title: Robust Layerwise Scaling Rules by Proper Weight Decay Tuning

🔹 Publication Date: Published on Oct 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.15262
• PDF: https://arxiv.org/pdf/2510.15262

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🔹 Title: DLER: Doing Length pEnalty Right - Incentivizing More Intelligence per Token via Reinforcement Learning

🔹 Publication Date: Published on Oct 16

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.15110
• PDF: https://arxiv.org/pdf/2510.15110

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