Arxiv Papers

Igor Melnyk
  • 5,0 (3)
  • SCIENCES
  • TOUS LES JOURS

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. -15 H

    [QA] Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs

    This paper explores filtering dual-use topics from training data to enhance the tamper-resistance of open-weight AI systems, demonstrating significant improvements in adversarial fine-tuning resistance without degrading unrelated capabilities. https://arxiv.org/abs//2508.06601 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 min

  2. -15 H

    Deep Ignorance: Filtering Pretraining Data Builds Tamper-Resistant Safeguards into Open-Weight LLMs

    This paper explores filtering dual-use topics from training data to enhance the tamper-resistance of open-weight AI systems, demonstrating significant improvements in adversarial fine-tuning resistance without degrading unrelated capabilities. https://arxiv.org/abs//2508.06601 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

    31 min

  3. -15 H

    [QA] Beyond Ten Turns: Unlocking Long-Horizon Agentic Search with Large-Scale Asynchronous RL

    This paper presents ASearcher, an open-source project enhancing search agents' capabilities through scalable RL training, achieving significant performance improvements in complex query handling and long-horizon search tasks. https://arxiv.org/abs//2508.07976 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 min

  4. -15 H

    Beyond Ten Turns: Unlocking Long-Horizon Agentic Search with Large-Scale Asynchronous RL

    This paper presents ASearcher, an open-source project enhancing search agents' capabilities through scalable RL training, achieving significant performance improvements in complex query handling and long-horizon search tasks. https://arxiv.org/abs//2508.07976 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

    28 min

  5. -2 J

    [QA] Part 1: Tricks or Traps? A Deep Dive into RL for LLM Reasoning

    https://arxiv.org/abs//2508.08221 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 min

  6. -2 J

    Part 1: Tricks or Traps? A Deep Dive into RL for LLM Reasoning

    https://arxiv.org/abs//2508.08221 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

    25 min

  7. -2 J

    [QA] MolmoAct: Action Reasoning Models that can Reason in Space

    Please provide the abstract you would like me to summarize. https://arxiv.org/abs//2508.07917 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 min

  8. -2 J

    MolmoAct: Action Reasoning Models that can Reason in Space

    https://arxiv.org/abs//2508.07917 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

    36 min
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Notes et avis

5
sur 5
3 notes

À propos

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

Informations

  • Création
    Igor Melnyk
  • Années d’activité
    2023 - 2025
  • Épisodes
    2 k
  • Classification
    Tous publics
  • Copyright
    © Igor Melnyk
  • Site web de l’émission
    Arxiv Papers

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