ML Research Hub – Telegram
ML Research Hub
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Advancing research in Machine Learning – practical insights, tools, and techniques for researchers.

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🔹 Title: Federated Computation of ROC and PR Curves

🔹 Publication Date: Published on Oct 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.04979
• PDF: https://arxiv.org/pdf/2510.04979
• Project Page: https://xuefeng-xu.github.io/fedcurve.html
• Github: https://github.com/xuefeng-xu/fedcurve

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🔹 Title: Fine-Tuning on Noisy Instructions: Effects on Generalization and Performance

🔹 Publication Date: Published on Oct 3

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.03528
• PDF: https://arxiv.org/pdf/2510.03528

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🔹 Title: Slow-Fast Policy Optimization: Reposition-Before-Update for LLM Reasoning

🔹 Publication Date: Published on Oct 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.04072
• PDF: https://arxiv.org/pdf/2510.04072
• Project Page: https://zkbig.github.io/Slow_Fast_Policy_Optimization.github.io/
• Github: https://zkbig.github.io/Slow_Fast_Policy_Optimization.github.io/

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🔹 Title: Prosperity before Collapse: How Far Can Off-Policy RL Reach with Stale Data on LLMs?

🔹 Publication Date: Published on Oct 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.01161
• PDF: https://arxiv.org/pdf/2510.01161

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🔹 Title: Position: Privacy Is Not Just Memorization!

🔹 Publication Date: Published on Oct 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.01645
• PDF: https://arxiv.org/pdf/2510.01645

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🔹 Title: Paris: A Decentralized Trained Open-Weight Diffusion Model

🔹 Publication Date: Published on Oct 3

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.03434
• PDF: https://arxiv.org/pdf/2510.03434

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🔹 Title: CWM: An Open-Weights LLM for Research on Code Generation with World Models

🔹 Publication Date: Published on Sep 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.02387
• PDF: https://arxiv.org/pdf/2510.02387

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🔹 Title: Optimized Minimal 4D Gaussian Splatting

🔹 Publication Date: Published on Oct 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.03857
• PDF: https://arxiv.org/pdf/2510.03857
• Project Page: https://minshirley.github.io/OMG4/
• Github: https://minshirley.github.io/OMG4/

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🔹 Title: Multilingual Routing in Mixture-of-Experts

🔹 Publication Date: Published on Oct 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.04694
• PDF: https://arxiv.org/pdf/2510.04694

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🔹 Title: TaTToo: Tool-Grounded Thinking PRM for Test-Time Scaling in Tabular Reasoning

🔹 Publication Date: Published on Oct 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/pdf/2510.06217
• PDF: https://arxiv.org/pdf/2510.06217

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🔹 Title: EgoNight: Towards Egocentric Vision Understanding at Night with a Challenging Benchmark

🔹 Publication Date: Published on Oct 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.06218
• PDF: https://arxiv.org/pdf/2510.06218

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🔹 Title: Deforming Videos to Masks: Flow Matching for Referring Video Segmentation

🔹 Publication Date: Published on Oct 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.06139
• PDF: https://arxiv.org/pdf/2510.06139

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🔹 Title: AInstein: Assessing the Feasibility of AI-Generated Approaches to Research Problems

🔹 Publication Date: Published on Oct 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.05432
• PDF: https://arxiv.org/pdf/2510.05432

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🔹 Title: Fast-dLLM v2: Efficient Block-Diffusion LLM

🔹 Publication Date: Published on Sep 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.26328
• PDF: https://arxiv.org/pdf/2509.26328

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🔹 Title: Margin Adaptive DPO: Leveraging Reward Model for Granular Control in Preference Optimization

🔹 Publication Date: Published on Oct 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.05342
• PDF: https://arxiv.org/pdf/2510.05342
• Github: https://github.com/sirano1004/Margin-Apative-Direct-Preference-Optimization

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🔹 Title: Demystifying deep search: a holistic evaluation with hint-free multi-hop questions and factorised metrics

🔹 Publication Date: Published on Oct 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.05137
• PDF: https://arxiv.org/pdf/2510.05137

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🔹 Title: HoloScene: Simulation-Ready Interactive 3D Worlds from a Single Video

🔹 Publication Date: Published on Oct 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.05560
• PDF: https://arxiv.org/pdf/2510.05560
• Project Page: https://xiahongchi.github.io/HoloScene/
• Github: https://github.com/xiahongchi/HoloScene

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🔹 Title: LightCache: Memory-Efficient, Training-Free Acceleration for Video Generation

🔹 Publication Date: Published on Oct 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.05367
• PDF: https://arxiv.org/pdf/2510.05367
• Github: https://github.com/NKUShaw/LightCache

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🔹 Title: Scaling Code-Assisted Chain-of-Thoughts and Instructions for Model Reasoning

🔹 Publication Date: Published on Oct 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.04081
• PDF: https://arxiv.org/pdf/2510.04081

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🔹 Title: A Contextual Quality Reward Model for Reliable and Efficient Best-of-N Sampling

🔹 Publication Date: Published on Oct 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.04087
• PDF: https://arxiv.org/pdf/2510.04087

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🔹 Title: DRIFT: Learning from Abundant User Dissatisfaction in Real-World Preference Learning

🔹 Publication Date: Published on Sep 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.02341
• PDF: https://arxiv.org/pdf/2510.02341

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