Arxiv Papers

Igor Melnyk
  • 4,8 (4)
  • 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. 1 SEPT.

    [QA] On the Theoretical Limitations of Embedding-Based Retrieval

    https://arxiv.org/abs//2508.21038 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 min

  2. 1 SEPT.

    On the Theoretical Limitations of Embedding-Based Retrieval

    https://arxiv.org/abs//2508.21038 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

    23 min

  3. 22 AOÛT

    [QA] Beyond GPT-5: Making LLMs Cheaper and Better via Performance–Efficiency Optimized Routing

    Avengers-Pro is a test-time routing framework that optimizes performance and efficiency in LLMs, achieving state-of-the-art results by dynamically assigning queries to suitable models based on performance-efficiency scores. https://arxiv.org/abs//2508.12631 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

  4. 22 AOÛT

    Beyond GPT-5: Making LLMs Cheaper and Better via Performance–Efficiency Optimized Routing

    Avengers-Pro is a test-time routing framework that optimizes performance and efficiency in LLMs, achieving state-of-the-art results by dynamically assigning queries to suitable models based on performance-efficiency scores. https://arxiv.org/abs//2508.12631 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 min

  5. 22 AOÛT

    [QA] Measuring the environmental impact of delivering AI at Google Scale

    https://arxiv.org/abs//2508.15734 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. 22 AOÛT

    Measuring the environmental impact of delivering AI at Google Scale

    https://arxiv.org/abs//2508.15734 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

    22 min

  7. 22 AOÛT

    [QA] Deep Think with Confidence

    DeepConf enhances reasoning efficiency and performance in Large Language Models by filtering low-quality traces using internal confidence signals, achieving high accuracy and reduced token generation without extra training. https://arxiv.org/abs//2508.15260 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. 22 AOÛT

    Deep Think with Confidence

    DeepConf enhances reasoning efficiency and performance in Large Language Models by filtering low-quality traces using internal confidence signals, achieving high accuracy and reduced token generation without extra training. https://arxiv.org/abs//2508.15260 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

    19 min
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Notes et avis

4,8
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4 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