Arxiv Papers

Igor Melnyk
Arxiv Papers

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. 18 HR. AGO

    [QA] Examining Two Hop Reasoning Through Information Content Scaling

    This study investigates transformers' inconsistent performance on two-hop questions, revealing that capacity scaling and generalization affect their ability to learn and answer these complex queries effectively. https://arxiv.org/abs//2502.03490 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

  2. 18 HR. AGO

    Examining Two Hop Reasoning Through Information Content Scaling

    This study investigates transformers' inconsistent performance on two-hop questions, revealing that capacity scaling and generalization affect their ability to learn and answer these complex queries effectively. https://arxiv.org/abs//2502.03490 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

    16 min

  3. 18 HR. AGO

    [QA] Gold-medalist Performance in Solving Olympiad Geometry with AlphaGeometry2

    https://arxiv.org/abs//2502.03544 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. 18 HR. AGO

    Gold-medalist Performance in Solving Olympiad Geometry with AlphaGeometry2

    https://arxiv.org/abs//2502.03544 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 min

  5. 1 DAY AGO

    [QA] Do Large Language Model Benchmarks Test Reliability?

    The paper highlights the lack of reliable benchmarks for large language models, proposing "platinum benchmarks" to minimize label errors and revealing persistent model failures in simple tasks. https://arxiv.org/abs//2502.03461 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

  6. 1 DAY AGO

    Do Large Language Model Benchmarks Test Reliability?

    The paper highlights the lack of reliable benchmarks for large language models, proposing "platinum benchmarks" to minimize label errors and revealing persistent model failures in simple tasks. https://arxiv.org/abs//2502.03461 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

  7. 1 DAY AGO

    Detecting Strategic Deception Using Linear Probes

    The study evaluates linear probes for detecting AI deception, achieving high accuracy in distinguishing honest from deceptive outputs, but concludes that current methods are insufficient for robust defense. https://arxiv.org/abs//2502.03407 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

  8. 2 DAYS AGO

    [QA] Evaluation of Large Language Models via Coupled Token Generation

    This paper argues for controlling randomization in evaluating large language models, showing that coupled autoregressive generation can yield different rankings than vanilla methods, despite fewer required samples. https://arxiv.org/abs//2502.01754 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
See All (1.9K)

Ratings & Reviews

5
out of 5
3 Ratings

About

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

Information

  • Creator
    Igor Melnyk
  • Years Active
    2023 - 2025
  • Episodes
    1.9K
  • Rating
    Clean
  • Copyright
    © Igor Melnyk
  • Show Website
    Arxiv Papers

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