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

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Controlled Self-Evolution for Algorithmic Code Optimization

📝 Summary:
Controlled Self-Evolution method improves code generation through diversified initialization, feedback-guided genetic evolution, and hierarchical memory to enhance exploration efficiency and solution ...

🔹 Publication Date: Published on Jan 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.07348
• PDF: https://arxiv.org/pdf/2601.07348

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SkinFlow: Efficient Information Transmission for Open Dermatological Diagnosis via Dynamic Visual Encoding and Staged RL

📝 Summary:
SkinFlow optimizes dermatological diagnosis by enhancing visual information transmission efficiency, addressing 'diffuse attention' in large models. It uses a Dynamic Vision Encoder and two-stage RL to significantly outperform massive general-purpose models, proving efficiency beats raw parameter...

🔹 Publication Date: Published on Jan 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09136
• PDF: https://arxiv.org/pdf/2601.09136

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Are LLMs Vulnerable to Preference-Undermining Attacks (PUA)? A Factorial Analysis Methodology for Diagnosing the Trade-off between Preference Alignment and Real-World Validity

📝 Summary:
Research examines how large language models can be manipulated through preference-undermining attacks that exploit alignment objectives, revealing model vulnerabilities and proposing a factorial evalu...

🔹 Publication Date: Published on Jan 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.06596
• PDF: https://arxiv.org/pdf/2601.06596

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FocusUI: Efficient UI Grounding via Position-Preserving Visual Token Selection

📝 Summary:
FocusUI is an efficient UI grounding framework that reduces computational overhead by selecting relevant visual tokens while preserving positional continuity through a novel PosPad strategy. AI-genera...

🔹 Publication Date: Published on Jan 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/pdf/2601.03928
• PDF: https://arxiv.org/pdf/2601.03928
• Github: https://github.com/showlab/FocusUI

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Efficient Camera-Controlled Video Generation of Static Scenes via Sparse Diffusion and 3D Rendering

📝 Summary:
Diffusion-based video generation is made more efficient through keyframe-based 3D reconstruction and rendering, enabling faster synthesis with maintained visual quality. AI-generated summary Modern vi...

🔹 Publication Date: Published on Jan 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09697
• PDF: https://arxiv.org/pdf/2601.09697

==================================

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DeepResearchEval: An Automated Framework for Deep Research Task Construction and Agentic Evaluation

📝 Summary:
DeepResearchEval presents an automated framework for creating complex research tasks and evaluating them through agent-based methods that adapt to task specifics and verify facts without relying on ci...

🔹 Publication Date: Published on Jan 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09688
• PDF: https://arxiv.org/pdf/2601.09688
• Github: https://github.com/Infinity-AILab/DeepResearchEval

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TranslateGemma Technical Report

📝 Summary:
TranslateGemma enhances Gemma 3's multilingual capabilities through two-stage fine-tuning with synthetic and human-translated data, achieving superior translation quality with improved efficiency. AI-...

🔹 Publication Date: Published on Jan 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09012
• PDF: https://arxiv.org/pdf/2601.09012

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OpenVoxel: Training-Free Grouping and Captioning Voxels for Open-Vocabulary 3D Scene Understanding

📝 Summary:
OpenVoxel enables open-vocabulary 3D scene understanding through training-free grouping and captioning of sparse voxels using Vision Language Models and Multi-modal Large Language Models. AI-generated...

🔹 Publication Date: Published on Jan 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09575
• PDF: https://arxiv.org/pdf/2601.09575

==================================

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EvoFSM: Controllable Self-Evolution for Deep Research with Finite State Machines

📝 Summary:
EvoFSM is a structured self-evolving framework for LLM agents that uses finite state machines to improve adaptability while maintaining control through constrained optimization and memory mechanisms. ...

🔹 Publication Date: Published on Jan 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09465
• PDF: https://arxiv.org/pdf/2601.09465

==================================

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The AI Hippocampus: How Far are We From Human Memory?

📝 Summary:
Memory mechanisms in large language models and multi-modal language models are categorized into implicit, explicit, and agentic paradigms, supporting enhanced reasoning, adaptability, and contextual f...

🔹 Publication Date: Published on Jan 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.09113
• PDF: https://arxiv.org/pdf/2601.09113

==================================

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