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Advancing research in Machine Learning – practical insights, tools, and techniques for researchers.

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ML Research Hub
🔹 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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🔹 Title: Discrete Diffusion Models with MLLMs for Unified Medical Multimodal Generation

🔹 Publication Date: Published on Oct 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.06131
• PDF: https://arxiv.org/pdf/2510.06131
• Project Page: https://github.com/UCSC-VLAA/MeDiM
• Github: https://github.com/UCSC-VLAA/MeDiM

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🔹 Title: VeriGuard: Enhancing LLM Agent Safety via Verified Code Generation

🔹 Publication Date: Published on Oct 3

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.05156
• PDF: https://arxiv.org/pdf/2510.05156

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🔹 Title: ASPO: Asymmetric Importance Sampling Policy Optimization

🔹 Publication Date: Published on Oct 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.06062
• PDF: https://arxiv.org/pdf/2510.06062
• Github: https://github.com/wizard-III/Archer2.0

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🔹 Title: Mixing Mechanisms: How Language Models Retrieve Bound Entities In-Context

🔹 Publication Date: Published on Oct 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.06182
• PDF: https://arxiv.org/pdf/2510.06182
• Project Page: https://yoav.ml/blog/2025/mixing-mechs/
• Github: https://github.com/yoavgur/mixing-mechs

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🔹 Title: CARE: Cognitive-reasoning Augmented Reinforcement for Emotional Support Conversation

🔹 Publication Date: Published on Sep 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.05122
• PDF: https://arxiv.org/pdf/2510.05122
• Project Page: https://github.com/aliyun/qwen-dianjin

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🚀 Release day: Qwen launched Qwen3-Omni — the first native end-to-end *omni-modal AI*

The model processes text, images, audio, and video in a single model.

On benchmarks, it looks like all modalities work with equal quality.

⚡️ Features
- First place in 22 out of 36 audio and multimodal benchmarks
- Support for 119 text languages,
- Minimal latency — 211 ms
- Audio processing up to 30 minutes long
- Allows flexible customization via system prompts
- Built-in tool calling

🌟 Open-source releases
The company released three versions:
- Qwen3-Omni-30B-A3B-Instruct
- Qwen3-Omni-30B-A3B-Thinking
- Qwen3-Omni-30B-A3B-Captioner

👉 You can try it here:

💬 Chat: https://chat.qwen.ai/?models=qwen3-omni-flash

👨‍💻 GitHub: https://github.com/QwenLM/Qwen3-Omni

🤗 Hugging Face: https://huggingface.co/collections/Qwen/qwen3-omni-68d100a86cd0906843ceccbe

🤖 ModelScope: https://modelscope.cn/collections/Qwen3-Omni-867aef131e7d4f

🎬 Demo: https://huggingface.co/spaces/Qwen/Qwen3-Omni-Demo

#qwen #opensource #llm #ml
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🔹 Title: Refusal Falls off a Cliff: How Safety Alignment Fails in Reasoning?

🔹 Publication Date: Published on Oct 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.06036
• PDF: https://arxiv.org/pdf/2510.06036

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🔹 Title: Fathom-DeepResearch: Unlocking Long Horizon Information Retrieval and Synthesis for SLMs

🔹 Publication Date: Published on Sep 28

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.24107
• PDF: https://arxiv.org/pdf/2509.24107

🔹 Datasets citing this paper:
• https://huggingface.co/datasets/FractalAIResearch/DuetQA-Verified
• https://huggingface.co/datasets/FractalAIResearch/DeepResearch-SFT

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🔹 Title: No Tokens Wasted: Leveraging Long Context in Biomedical Vision-Language Models

🔹 Publication Date: Published on Oct 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.03978
• PDF: https://arxiv.org/pdf/2510.03978
• Github: https://github.com/minwoosun/open_clip_bmc

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🔹 Title: MixReasoning: Switching Modes to Think

🔹 Publication Date: Published on Oct 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.06052
• PDF: https://arxiv.org/pdf/2510.06052

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🔹 Title: Human3R: Everyone Everywhere All at Once

🔹 Publication Date: Published on Oct 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.06219
• PDF: https://arxiv.org/pdf/2510.06219
• Github: https://fanegg.github.io/Human3R/

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🔹 Title: Distributional Semantics Tracing: A Framework for Explaining Hallucinations in Large Language Models

🔹 Publication Date: Published on Oct 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.06107
• PDF: https://arxiv.org/pdf/2510.06107

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🔹 Title: Revisiting Modeling and Evaluation Approaches in Speech Emotion Recognition: Considering Subjectivity of Annotators and Ambiguity of Emotions

🔹 Publication Date: Published on Oct 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.05934
• PDF: https://arxiv.org/pdf/2510.05934

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🔹 Title: HalluGuard: Evidence-Grounded Small Reasoning Models to Mitigate Hallucinations in Retrieval-Augmented Generation

🔹 Publication Date: Published on Oct 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.00880
• PDF: https://arxiv.org/pdf/2510.00880

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