🔹 Title: Emu3.5: Native Multimodal Models are World Learners

🔹 Publication Date: Published on Oct 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.26583
• PDF: https://arxiv.org/pdf/2510.26583
• Project Page: https://emu.world/
• Github: https://github.com/baaivision/Emu3.5

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🔹 Title: Are Video Models Ready as Zero-Shot Reasoners? An Empirical Study with the MME-CoF Benchmark

🔹 Publication Date: Published on Oct 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.26802
• PDF: https://arxiv.org/pdf/2510.26802
• Github: https://video-cof.github.io/

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🔹 Title: Remote Labor Index: Measuring AI Automation of Remote Work

🔹 Publication Date: Published on Oct 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.26787
• PDF: https://arxiv.org/pdf/2510.26787

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🔹 Title: Can Agent Conquer Web? Exploring the Frontiers of ChatGPT Atlas Agent in Web Games

🔹 Publication Date: Published on Oct 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.26298
• PDF: https://arxiv.org/pdf/2510.26298
• Project Page: https://atlas-game-eval.github.io/

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🔹 Title: Supervised Reinforcement Learning: From Expert Trajectories to Step-wise Reasoning

🔹 Publication Date: Published on Oct 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.25992
• PDF: https://arxiv.org/pdf/2510.25992

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🔹 Title: Counteracting Matthew Effect in Self-Improvement of LVLMs through Head-Tail Re-balancing

🔹 Publication Date: Published on Oct 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.26474
• PDF: https://arxiv.org/pdf/2510.26474

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🔹 Title: OmniX: From Unified Panoramic Generation and Perception to Graphics-Ready 3D Scenes

🔹 Publication Date: Published on Oct 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.26800
• PDF: https://arxiv.org/pdf/2510.26800
• Project Page: https://yukun-huang.github.io/OmniX/
• Github: https://yukun-huang.github.io/OmniX/

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🔹 Title: The Quest for Generalizable Motion Generation: Data, Model, and Evaluation

🔹 Publication Date: Published on Oct 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.26794
• PDF: https://arxiv.org/pdf/2510.26794

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🔹 Title: EnzyControl: Adding Functional and Substrate-Specific Control for Enzyme Backbone Generation

🔹 Publication Date: Published on Oct 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.25132
• PDF: https://arxiv.org/pdf/2510.25132

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🔹 Title: CRAG-MM: Multi-modal Multi-turn Comprehensive RAG Benchmark

🔹 Publication Date: Published on Oct 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.26160
• PDF: https://arxiv.org/pdf/2510.26160

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🔹 Title: FullPart: Generating each 3D Part at Full Resolution

🔹 Publication Date: Published on Oct 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.26140
• PDF: https://arxiv.org/pdf/2510.26140
• Project Page: https://fullpart3d.github.io/
• Github: https://github.com/hkdsc/fullpart

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🔹 Title: Magentic Marketplace: An Open-Source Environment for Studying Agentic Markets

🔹 Publication Date: Published on Oct 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.25779
• PDF: https://arxiv.org/pdf/2510.25779
• Github: https://github.com/microsoft/multi-agent-marketplace

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🔹 Title: AMO-Bench: Large Language Models Still Struggle in High School Math Competitions

🔹 Publication Date: Published on Oct 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/pdf/2510.26768
• PDF: https://arxiv.org/pdf/2510.26768
• Project Page: https://amo-bench.github.io/
• Github: https://amo-bench.github.io/

🔹 Datasets citing this paper:
• https://huggingface.co/datasets/meituan-longcat/AMO-Bench

🔹 Spaces citing this paper:
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🔹 Title: EHR-R1: A Reasoning-Enhanced Foundational Language Model for Electronic Health Record Analysis

🔹 Publication Date: Published on Oct 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.25628
• PDF: https://arxiv.org/pdf/2510.25628
• Github: https://github.com/MAGIC-AI4Med/EHR-R1

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A noscript

I guess this is a start
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🔹 Title: The Era of Agentic Organization: Learning to Organize with Language Models

🔹 Publication Date: Published on Oct 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.26658
• PDF: https://arxiv.org/pdf/2510.26658

🔹 Datasets citing this paper:
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🔹 Title: OmniLayout: Enabling Coarse-to-Fine Learning with LLMs for Universal Document Layout Generation

🔹 Publication Date: Published on Oct 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.26213
• PDF: https://arxiv.org/pdf/2510.26213

🔹 Datasets citing this paper:
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🔹 Title: Exploring Conditions for Diffusion models in Robotic Control

🔹 Publication Date: Published on Oct 17

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.15510
• PDF: https://arxiv.org/pdf/2510.15510
• Project Page: https://orca-rc.github.io/
• Github: https://orca-rc.github.io/

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🔹 Title: ChartAB: A Benchmark for Chart Grounding & Dense Alignment

🔹 Publication Date: Published on Oct 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.26781
• PDF: https://arxiv.org/pdf/2510.26781
• Project Page: https://huggingface.co/datasets/umd-zhou-lab/ChartAlignBench
• Github: https://github.com/tianyi-lab/ChartAlignBench

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🔹 Title: MIRO: MultI-Reward cOnditioned pretraining improves T2I quality and efficiency

🔹 Publication Date: Published on Oct 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.25897
• PDF: https://arxiv.org/pdf/2510.25897
• Project Page: https://nicolas-dufour.github.io/miro/
• Github: https://nicolas-dufour.github.io/miro/

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