Arxiv Papers

Igor Melnyk

Running out of time to catch up with new arXiv papers? We take the most impactful papers and present them as convenient podcasts. If you're a visual learner, we offer these papers in an engaging video format. Our service fills the gap between overly brief paper summaries and time-consuming full paper reads. You gain academic insights in a time-efficient, digestible format. Code behind this work: https://github.com/imelnyk/ArxivPapers

  1. 2 NGÀY TRƯỚC

    [QA] Advancing Event Forecasting through Massive Training of Large Language Models: Challenges, Solutions, and Broader Impacts

    The paper advocates for research on training superforecaster-level event forecasting LLMs, addressing challenges in training methods and data acquisition to enhance predictive intelligence capabilities. https://arxiv.org/abs//2507.19477 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016 Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers

    10 phút

  2. 2 NGÀY TRƯỚC

    Advancing Event Forecasting through Massive Training of Large Language Models: Challenges, Solutions, and Broader Impacts

    The paper advocates for research on training superforecaster-level event forecasting LLMs, addressing challenges in training methods and data acquisition to enhance predictive intelligence capabilities. https://arxiv.org/abs//2507.19477 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016 Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers

    58 phút

  3. 2 NGÀY TRƯỚC

    [QA] AlphaGo Moment for Model Architecture Discovery

    ASI-ARCH is an autonomous AI system that innovates neural architecture discovery, surpassing human limitations and achieving state-of-the-art designs through extensive experimentation and scalable computational processes. https://arxiv.org/abs//2507.18074 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016 Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers

    8 phút

  4. 2 NGÀY TRƯỚC

    AlphaGo Moment for Model Architecture Discovery

    ASI-ARCH is an autonomous AI system that innovates neural architecture discovery, surpassing human limitations and achieving state-of-the-art designs through extensive experimentation and scalable computational processes. https://arxiv.org/abs//2507.18074 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016 Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers

    24 phút

  5. 2 NGÀY TRƯỚC

    [QA] Learning without training: The implicit dynamics of in-context learning

    This paper explores how stacking a self-attention layer with an MLP in transformers enables Large Language Models to learn in context by implicitly modifying MLP weights based on presented examples. https://arxiv.org/abs//2507.16003 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016 Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers

    9 phút

  6. 2 NGÀY TRƯỚC

    Learning without training: The implicit dynamics of in-context learning

    This paper explores how stacking a self-attention layer with an MLP in transformers enables Large Language Models to learn in context by implicitly modifying MLP weights based on presented examples. https://arxiv.org/abs//2507.16003 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016 Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers

    13 phút

  7. 4 NGÀY TRƯỚC

    [QA] NABLA: Neighborhood Adaptive Block-Level Attention

    NABLA introduces a Neighborhood Adaptive Block-Level Attention mechanism for video diffusion transformers, enhancing efficiency and speed while maintaining quality, achieving up to 2.7 times faster training and inference. https://arxiv.org/abs//2507.13546 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016 Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers

    7 phút

  8. 4 NGÀY TRƯỚC

    NABLA: Neighborhood Adaptive Block-Level Attention

    NABLA introduces a Neighborhood Adaptive Block-Level Attention mechanism for video diffusion transformers, enhancing efficiency and speed while maintaining quality, achieving up to 2.7 times faster training and inference. https://arxiv.org/abs//2507.13546 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016 Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers

    13 phút
Xem tất cả (2 N)

Xếp Hạng & Nhận Xét

5
/5
3 Xếp hạng

Giới Thiệu

Running out of time to catch up with new arXiv papers? We take the most impactful papers and present them as convenient podcasts. If you're a visual learner, we offer these papers in an engaging video format. Our service fills the gap between overly brief paper summaries and time-consuming full paper reads. You gain academic insights in a time-efficient, digestible format. Code behind this work: https://github.com/imelnyk/ArxivPapers

Thông Tin

  • Nhà sáng tạo
    Igor Melnyk
  • Năm hoạt động
    2023 - 2025
  • Tập
    2 N
  • Xếp hạng
    Sạch
  • Bản quyền
    © Igor Melnyk
  • Trang web chương trình
    Arxiv Papers

Có Thể Bạn Cũng Thích