Arxiv Papers

Igor Melnyk
  • ٥٫٠ (٣)
  • العلوم
  • يتم التحديث يوميًا
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. قبل ١٥ ساعة

    [QA] GenRecal: Generation after Recalibration from Large to Small Vision-Language Models

    GenRecal is a novel distillation framework for vision-language models that enhances knowledge transfer across diverse architectures, improving performance on resource-constrained devices while outperforming large-scale VLMs. https://arxiv.org/abs//2506.15681 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

    ٨ من الدقائق

  2. قبل ١٥ ساعة

    GenRecal: Generation after Recalibration from Large to Small Vision-Language Models

    GenRecal is a novel distillation framework for vision-language models that enhances knowledge transfer across diverse architectures, improving performance on resource-constrained devices while outperforming large-scale VLMs. https://arxiv.org/abs//2506.15681 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

    ١٧ من الدقائق

  3. قبل ١٥ ساعة

    [QA] ProtoReasoning: Prototypes as the Foundation for Generalizable Reasoning in LLMs

    https://arxiv.org/abs//2506.15211 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

    ٩ من الدقائق

  4. قبل ١٥ ساعة

    ProtoReasoning: Prototypes as the Foundation for Generalizable Reasoning in LLMs

    https://arxiv.org/abs//2506.15211 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

    ١٢ من الدقائق

  5. قبل يومين

    [QA] Sampling from Your Language Model One Byte at a Time

    This paper presents a method to convert autoregressive language models with BPE tokenizers into character-level models, addressing tokenization issues and enabling model interoperability and improved performance through ensemble and proxy-tuning. https://arxiv.org/abs//2506.14123 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

    ٧ من الدقائق

  6. قبل يومين

    Sampling from Your Language Model One Byte at a Time

    This paper presents a method to convert autoregressive language models with BPE tokenizers into character-level models, addressing tokenization issues and enabling model interoperability and improved performance through ensemble and proxy-tuning. https://arxiv.org/abs//2506.14123 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

    ١٤ من الدقائق

  7. قبل يومين

    [QA] Don't throw the baby out with the bathwater: How and why deep learning for ARC

    This paper demonstrates that deep learning, through on-the-fly training and innovative techniques, significantly enhances performance on the Abstraction and Reasoning Corpus, achieving state-of-the-art results. https://arxiv.org/abs//2506.14276 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

    ٨ من الدقائق

  8. قبل يومين

    Don't throw the baby out with the bathwater: How and why deep learning for ARC

    This paper demonstrates that deep learning, through on-the-fly training and innovative techniques, significantly enhances performance on the Abstraction and Reasoning Corpus, achieving state-of-the-art results. https://arxiv.org/abs//2506.14276 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

    ٣٣ من الدقائق
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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

المعلومات

  • صناع العمل
    Igor Melnyk
  • سنوات النشاط
    ٢٠٢٣ - ٢٠٢٥
  • الحلقات
    ٢ ألف
  • التقييم
    ملائم
  • حقوق النشر
    © Igor Melnyk
  • موقع البرنامج على الويب
    Arxiv Papers

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