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: DiffTester: Accelerating Unit Test Generation for Diffusion LLMs via Repetitive Pattern

🔹 Publication Date: Published on Sep 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.24975
• PDF: https://arxiv.org/pdf/2509.24975
• Github: https://github.com/wellbeingyang/DLM4UTG-open

🔹 Datasets citing this paper:
https://huggingface.co/datasets/wellbeing/TestEval-extend

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🔹 Title: Scaling Policy Compliance Assessment in Language Models with Policy Reasoning Traces

🔹 Publication Date: Published on Sep 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.23291
• PDF: https://arxiv.org/pdf/2509.23291

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🔹 Title: TalkPlay-Tools: Conversational Music Recommendation with LLM Tool Calling

🔹 Publication Date: Published on Oct 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.01698
• PDF: https://arxiv.org/pdf/2510.01698
• Project Page: https://talkpl.ai/p/talkplay_tools/index.html
• Github: https://github.com/talkpl-ai/talkplay-tools

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🔹 Title: Large Reasoning Models Learn Better Alignment from Flawed Thinking

🔹 Publication Date: Published on Oct 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.00938
• PDF: https://arxiv.org/pdf/2510.00938

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1
🔹 Title: Game-Time: Evaluating Temporal Dynamics in Spoken Language Models

🔹 Publication Date: Published on Sep 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.26388
• PDF: https://arxiv.org/pdf/2509.26388
• Project Page: https://ga642381.github.io/Game-Time
• Github: https://ga642381.github.io/Game-Time

🔹 Datasets citing this paper:
https://huggingface.co/datasets/gametime-benchmark/gametime

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🔹 Title: Consolidating Reinforcement Learning for Multimodal Discrete Diffusion Models

🔹 Publication Date: Published on Oct 3

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.02880
• PDF: https://arxiv.org/pdf/2510.02880
• Github: https://github.com/martian422/MaskGRPO

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🔹 Title: Bridging the Gap Between Promise and Performance for Microscaling FP4 Quantization

🔹 Publication Date: Published on Sep 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.23202
• PDF: https://arxiv.org/pdf/2509.23202

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🔹 Title: Pretraining with hierarchical memories: separating long-tail and common knowledge

🔹 Publication Date: Published on Sep 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.02375
• PDF: https://arxiv.org/pdf/2510.02375

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🔹 Title: SoundReactor: Frame-level Online Video-to-Audio Generation

🔹 Publication Date: Published on Oct 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.02110
• PDF: https://arxiv.org/pdf/2510.02110
• Project Page: https://koichi-saito-sony.github.io/soundreactor/
• Github: https://koichi-saito-sony.github.io/soundreactor/

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🔹 Title: Continuously Augmented Discrete Diffusion model for Categorical Generative Modeling

🔹 Publication Date: Published on Oct 1

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.01329
• PDF: https://arxiv.org/pdf/2510.01329

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1
🔹 Title: Personalized Reasoning: Just-In-Time Personalization and Why LLMs Fail At It

🔹 Publication Date: Published on Sep 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.00177
• PDF: https://arxiv.org/pdf/2510.00177

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🔹 Title: Dale meets Langevin: A Multiplicative Denoising Diffusion Model

🔹 Publication Date: Published on Oct 3

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.02730
• PDF: https://arxiv.org/pdf/2510.02730

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1
🔹 Title: Less LLM, More Documents: Searching for Improved RAG

🔹 Publication Date: Published on Oct 3

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.02657
• PDF: https://arxiv.org/pdf/2510.02657

🔹 Datasets citing this paper:
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🔹 Title: OpenTSLM: Time-Series Language Models for Reasoning over Multivariate Medical Text- and Time-Series Data

🔹 Publication Date: Published on Oct 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.02410
• PDF: https://arxiv.org/pdf/2510.02410

🔹 Datasets citing this paper:
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🔹 Title: Efficient Test-Time Scaling for Small Vision-Language Models

🔹 Publication Date: Published on Oct 3

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.03574
• PDF: https://arxiv.org/pdf/2510.03574
• Project Page: https://monurcan.github.io/efficient_test_time_scaling
• Github: https://github.com/monurcan/efficient_test_time_scaling

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🔹 Title: Utility-Learning Tension in Self-Modifying Agents

🔹 Publication Date: Published on Oct 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.04399
• PDF: https://arxiv.org/pdf/2510.04399

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🔹 Title: Reactive Transformer (RxT) -- Stateful Real-Time Processing for Event-Driven Reactive Language Models

🔹 Publication Date: Published on Oct 3

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.03561
• PDF: https://arxiv.org/pdf/2510.03561
• Project Page: https://rxai.dev/research/reactive-transformer-introduction
• Github: https://github.com/RxAI-dev/rxlm

🔹 Datasets citing this paper:
https://huggingface.co/datasets/ReactiveAI/TinyStories-MRL
https://huggingface.co/datasets/ReactiveAI/TinyStories-Plus-Interaction-SFT

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🔹 Title: Front-Loading Reasoning: The Synergy between Pretraining and Post-Training Data

🔹 Publication Date: Published on Sep 26

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.03264
• PDF: https://arxiv.org/pdf/2510.03264

🔹 Datasets citing this paper:
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🔹 Title: Paper2Video: Automatic Video Generation from Scientific Papers

🔹 Publication Date: Published on Oct 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.05096
• PDF: https://arxiv.org/pdf/2510.05096
• Project Page: https://showlab.github.io/Paper2Video/
• Github: https://showlab.github.io/Paper2Video/

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🔹 Title: Judging with Confidence: Calibrating Autoraters to Preference Distributions

🔹 Publication Date: Published on Sep 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.00263
• PDF: https://arxiv.org/pdf/2510.00263

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🔹 Title: Video-LMM Post-Training: A Deep Dive into Video Reasoning with Large Multimodal Models

🔹 Publication Date: Published on Oct 6

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.05034
• PDF: https://arxiv.org/pdf/2510.05034
• Github: https://github.com/yunlong10/Awesome-Video-LMM-Post-Training

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