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: AU-Harness: An Open-Source Toolkit for Holistic Evaluation of Audio LLMs

🔹 Publication Date: Published on Sep 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.08031
• PDF: https://arxiv.org/pdf/2509.08031
• Project Page: https://au-harness.github.io/
• Github: https://github.com/ServiceNow/AU-Harness

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🔹 Title: Spatial Reasoning with Vision-Language Models in Ego-Centric Multi-View Scenes

🔹 Publication Date: Published on Sep 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.06266
• PDF: https://arxiv.org/pdf/2509.06266
• Project Page: https://vbdi.github.io/Ego3D-Bench-webpage/
• Github: https://github.com/vbdi/Ego3D-Bench

🔹 Datasets citing this paper:
https://huggingface.co/datasets/vbdai/Ego3D-Bench

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🔹 Title: MachineLearningLM: Continued Pretraining Language Models on Millions of Synthetic Tabular Prediction Tasks Scales In-Context ML

🔹 Publication Date: Published on Sep 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.06806
• PDF: https://arxiv.org/pdf/2509.06806
• Project Page: https://huggingface.co/MachineLearningLM/
• Github: https://github.com/HaoAreYuDong/MachineLearningLM

🔹 Datasets citing this paper:
https://huggingface.co/datasets/MachineLearningLM/machinelearninglm-scm-synthetic-tabularml

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🚀🔥 𝗕𝗲𝗰𝗼𝗺𝗲 𝗮𝗻 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 𝗕𝘂𝗶𝗹𝗱𝗲𝗿 — 𝗙𝗿𝗲𝗲 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗣𝗿𝗼𝗴𝗿𝗮𝗺
Master the hottest skill in tech: building intelligent AI systems that think and act independently.

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ML Research Hub pinned «🚀🔥 𝗕𝗲𝗰𝗼𝗺𝗲 𝗮𝗻 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 𝗕𝘂𝗶𝗹𝗱𝗲𝗿 — 𝗙𝗿𝗲𝗲 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗣𝗿𝗼𝗴𝗿𝗮𝗺 Master the hottest skill in tech: building intelligent AI systems that think and act independently. Learn to build smart 𝗰𝗵𝗮𝘁𝗯𝗼𝘁𝘀, 𝗔𝗜 𝗮𝘀𝘀𝗶𝘀𝘁𝗮𝗻𝘁𝘀 𝗮𝗻𝗱 𝗺𝘂𝗹𝘁𝗶-𝗮𝗴𝗲𝗻𝘁 𝘀𝘆𝘀𝘁𝗲𝗺𝘀. 𝗘𝗮𝗿𝗻 𝗽𝗿𝗼𝗳𝗲𝘀𝘀𝗶𝗼𝗻𝗮𝗹 𝗰𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻…»
🔹 Title: The Illusion of Diminishing Returns: Measuring Long Horizon Execution in LLMs

🔹 Publication Date: Published on Sep 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.09677
• PDF: https://arxiv.org/pdf/2509.09677

🔹 Datasets citing this paper:
https://huggingface.co/datasets/arvindh75/Long-Horizon-Execution

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🔹 Title: InfGen: A Resolution-Agnostic Paradigm for Scalable Image Synthesis

🔹 Publication Date: Published on Sep 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.10441
• PDF: https://arxiv.org/pdf/2509.10441

🔹 Datasets citing this paper:
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🔹 Title: Color Me Correctly: Bridging Perceptual Color Spaces and Text Embeddings for Improved Diffusion Generation

🔹 Publication Date: Published on Sep 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.10058
• PDF: https://arxiv.org/pdf/2509.10058

🔹 Datasets citing this paper:
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🔹 Title: QuantAgent: Price-Driven Multi-Agent LLMs for High-Frequency Trading

🔹 Publication Date: Published on Sep 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.09995
• PDF: https://arxiv.org/pdf/2509.09995

🔹 Datasets citing this paper:
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🔹 Title: MCP-AgentBench: Evaluating Real-World Language Agent Performance with MCP-Mediated Tools

🔹 Publication Date: Published on Sep 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.09734
• PDF: https://arxiv.org/pdf/2509.09734

🔹 Datasets citing this paper:
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🔹 Title: VStyle: A Benchmark for Voice Style Adaptation with Spoken Instructions

🔹 Publication Date: Published on Sep 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.09716
• PDF: https://arxiv.org/pdf/2509.09716
• Project Page: https://junzhan2000.github.io/VStyle.github.io/
• Github: https://github.com/alibaba/vstyle

🔹 Datasets citing this paper:
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🔹 Title: Virtual Agent Economies

🔹 Publication Date: Published on Sep 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.10147
• PDF: https://arxiv.org/pdf/2509.10147

🔹 Datasets citing this paper:
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🔹 Title: LoFT: Parameter-Efficient Fine-Tuning for Long-tailed Semi-Supervised Learning in Open-World Scenarios

🔹 Publication Date: Published on Sep 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.09926
• PDF: https://arxiv.org/pdf/2509.09926

🔹 Datasets citing this paper:
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🔹 Title: HANRAG: Heuristic Accurate Noise-resistant Retrieval-Augmented Generation for Multi-hop Question Answering

🔹 Publication Date: Published on Sep 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.09713
• PDF: https://arxiv.org/pdf/2509.09713

🔹 Datasets citing this paper:
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🔹 Title: Inpainting-Guided Policy Optimization for Diffusion Large Language Models

🔹 Publication Date: Published on Sep 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.10396
• PDF: https://arxiv.org/pdf/2509.10396

🔹 Datasets citing this paper:
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🔹 Title: CMHG: A Dataset and Benchmark for Headline Generation of Minority Languages in China

🔹 Publication Date: Published on Sep 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.09990
• PDF: https://arxiv.org/pdf/2509.09990

🔹 Datasets citing this paper:
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🔹 Title: X-Part: high fidelity and structure coherent shape decomposition

🔹 Publication Date: Published on Sep 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.08643
• PDF: https://arxiv.org/pdf/2509.08643

🔹 Datasets citing this paper:
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🔹 Title: IntrEx: A Dataset for Modeling Engagement in Educational Conversations

🔹 Publication Date: Published on Sep 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.06652
• PDF: https://arxiv.org/pdf/2509.06652
• Github: https://github.com/Xingwei-Tan/IntrEx

🔹 Datasets citing this paper:
https://huggingface.co/datasets/XingweiT/IntrEx-sequence
https://huggingface.co/datasets/XingweiT/IntrEx-turn

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🔹 Title: FLOWER: Democratizing Generalist Robot Policies with Efficient Vision-Language-Action Flow Policies

🔹 Publication Date: Published on Sep 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.04996
• PDF: https://arxiv.org/pdf/2509.04996

🔹 Datasets citing this paper:
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🔹 Title: DeMeVa at LeWiDi-2025: Modeling Perspectives with In-Context Learning and Label Distribution Learning

🔹 Publication Date: Published on Sep 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.09524
• PDF: https://arxiv.org/pdf/2509.09524

🔹 Datasets citing this paper:
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