Knowledge Distillation and Dataset Distillation of Large Language Models: Emerging Trends, Challenges, and Future Directions · HackerPapers discussionshttps://hackerpaper.kaipfister.de/p/2504.14772/Collected HN comments and submissions linking this paper.enMon, 02 Nov 2026 11:16:22 GMTKnowledge Distillation and Dataset Distillation of Large Language Models: Emerging Trends, Challenges, and Future Directions — mentioned by credit_guyhttps://news.ycombinator.com/item?id=46068607urn:hackerpapers:mention:2504.14772:46068607Thu, 27 Nov 2025 12:23:36 GMT<p>It is just much more efficient to train on synthetic data. When you train on real data, all you know is the next token. With synthetic data you know the probability distribution of the next token; this results in a multiplier effect, and sometimes this effect is dramatic. [1] https://arxiv.org/pdf/2504.14772v1</p><p><a href="https://hackerpaper.kaipfister.de/p/2504.14772/">Paper and discussion history</a>. A mention is not an endorsement.</p>cs.CL