Data Science | Machine Learning with Python for Researchers
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πŸ”Ή Title: ARE: Scaling Up Agent Environments and Evaluations

πŸ”Ή Publication Date: Published on Sep 21

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2509.17158
β€’ PDF: https://arxiv.org/pdf/2509.17158

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πŸ”Ή Title: From Hugging Face to GitHub: Tracing License Drift in the Open-Source AI Ecosystem

πŸ”Ή Publication Date: Published on Sep 11

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2509.09873
β€’ PDF: https://arxiv.org/pdf/2509.09873
β€’ Project Page: https://huggingface.co/papers?q=GitHub%20projects

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πŸ“Œ Paper Walkthrough: Attention Is All You Need

πŸ—‚ Category: DEEP LEARNING

πŸ•’ Date: 2024-11-03 | ⏱️ Read time: 46 min read

The complete guide to implementing a Transformer from scratch
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πŸ”Ή Title: LIMI: Less is More for Agency

πŸ”Ή Publication Date: Published on Sep 22

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2509.17567
β€’ PDF: https://arxiv.org/pdf/2509.17567
β€’ Project Page: https://github.com/GAIR-NLP/LIMI
β€’ Github: https://github.com/GAIR-NLP/LIMI

πŸ”Ή Datasets citing this paper:
β€’ https://huggingface.co/datasets/GAIR/LIMI

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πŸ”Ή Title: StereoAdapter: Adapting Stereo Depth Estimation to Underwater Scenes

πŸ”Ή Publication Date: Published on Sep 19

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2509.16415
β€’ PDF: https://arxiv.org/pdf/2509.16415
β€’ Project Page: https://aigeeksgroup.github.io/StereoAdapter/
β€’ Github: https://github.com/AIGeeksGroup/StereoAdapter

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πŸ”Ή Title: Understanding Embedding Scaling in Collaborative Filtering

πŸ”Ή Publication Date: Published on Sep 19

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2509.15709
β€’ PDF: https://arxiv.org/pdf/2509.15709

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πŸ”Ή Title: AuditoryBench++: Can Language Models Understand Auditory Knowledge without Hearing?

πŸ”Ή Publication Date: Published on Sep 22

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2509.17641
β€’ PDF: https://arxiv.org/pdf/2509.17641
β€’ Github: https://auditorybenchpp.github.io/

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πŸ”Ή Title: When Big Models Train Small Ones: Label-Free Model Parity Alignment for Efficient Visual Question Answering using Small VLMs

πŸ”Ή Publication Date: Published on Sep 20

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2509.16633
β€’ PDF: https://arxiv.org/pdf/2509.16633
β€’ Github: https://github.com/vl2g/MPA

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πŸ”Ή Title: From Uniform to Heterogeneous: Tailoring Policy Optimization to Every Token's Nature

πŸ”Ή Publication Date: Published on Sep 20

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2509.16591
β€’ PDF: https://arxiv.org/pdf/2509.16591
β€’ Github: https://github.com/starriver030515/HAPO

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πŸ”Ή Title: MetaEmbed: Scaling Multimodal Retrieval at Test-Time with Flexible Late Interaction

πŸ”Ή Publication Date: Published on Sep 22

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2509.18095
β€’ PDF: https://arxiv.org/pdf/2509.18095

πŸ”Ή Datasets citing this paper:
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πŸ”Ή Title: GeoPQA: Bridging the Visual Perception Gap in MLLMs for Geometric Reasoning

πŸ”Ή Publication Date: Published on Sep 22

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2509.17437
β€’ PDF: https://arxiv.org/pdf/2509.17437

πŸ”Ή Datasets citing this paper:
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πŸ”Ή Title: VaseVQA: Multimodal Agent and Benchmark for Ancient Greek Pottery

πŸ”Ή Publication Date: Published on Sep 21

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2509.17191
β€’ PDF: https://arxiv.org/pdf/2509.17191

πŸ”Ή Datasets citing this paper:
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πŸ”Ή Title: TempSamp-R1: Effective Temporal Sampling with Reinforcement Fine-Tuning for Video LLMs

πŸ”Ή Publication Date: Published on Sep 22

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2509.18056
β€’ PDF: https://arxiv.org/pdf/2509.18056

πŸ”Ή Datasets citing this paper:
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πŸ”Ή Title: Turk-LettuceDetect: A Hallucination Detection Models for Turkish RAG Applications

πŸ”Ή Publication Date: Published on Sep 22

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2509.17671
β€’ PDF: https://arxiv.org/pdf/2509.17671

πŸ”Ή Datasets citing this paper:
β€’ https://huggingface.co/datasets/newmindai/RAGTruth-TR

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πŸ”Ή Title: CodeFuse-CR-Bench: A Comprehensiveness-aware Benchmark for End-to-End Code Review Evaluation in Python Projects

πŸ”Ή Publication Date: Published on Sep 18

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2509.14856
β€’ PDF: https://arxiv.org/pdf/2509.14856

πŸ”Ή Datasets citing this paper:
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πŸ”Ή Title: SCAN: Self-Denoising Monte Carlo Annotation for Robust Process Reward Learning

πŸ”Ή Publication Date: Published on Sep 20

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2509.16548
β€’ PDF: https://arxiv.org/pdf/2509.16548

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πŸ”Ή Title: QWHA: Quantization-Aware Walsh-Hadamard Adaptation for Parameter-Efficient Fine-Tuning on Large Language Models

πŸ”Ή Publication Date: Published on Sep 22

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2509.17428
β€’ PDF: https://arxiv.org/pdf/2509.17428
β€’ Github: https://github.com/vantaa89/qwha

πŸ”Ή Datasets citing this paper:
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πŸ”Ή Title: Reasoning Core: A Scalable RL Environment for LLM Symbolic Reasoning

πŸ”Ή Publication Date: Published on Sep 22

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2509.18083
β€’ PDF: https://arxiv.org/pdf/2509.18083
β€’ Project Page: https://github.com/sileod/reasoning_core
β€’ Github: https://github.com/sileod/reasoning_core

πŸ”Ή Datasets citing this paper:
β€’ https://huggingface.co/datasets/reasoning-core/rc1

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πŸ”Ή Title: FlagEval Findings Report: A Preliminary Evaluation of Large Reasoning Models on Automatically Verifiable Textual and Visual Questions

πŸ”Ή Publication Date: Published on Sep 21

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2509.17177
β€’ PDF: https://arxiv.org/pdf/2509.17177

πŸ”Ή Datasets citing this paper:
β€’ https://huggingface.co/datasets/BAAI/ROME

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πŸ”Ή Title: DIWALI - Diversity and Inclusivity aWare cuLture specific Items for India: Dataset and Assessment of LLMs for Cultural Text Adaptation in Indian Context

πŸ”Ή Publication Date: Published on Sep 22

πŸ”Ή Paper Links:
β€’ arXiv Page: https://arxiv.org/abs/2509.17399
β€’ PDF: https://arxiv.org/pdf/2509.17399
β€’ Project Page: https://nlip-lab.github.io/nlip/publications/diwali/
β€’ Github: https://huggingface.co/papers/!https:/github.com/pramitsahoo/culture-evaluation

πŸ”Ή Datasets citing this paper:
β€’ https://huggingface.co/datasets/nlip/DIWALI

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