arxiv
PublishedOctober 22, 2026 at 4:00 AM
How Much Gradient Does Truncated Backprop Lose in Looped Transformers?
Publisher summary· verbatim
arXiv:2610.28871v1 Announce Type: new Abstract: Looped transformers reuse one block of layers many times and are often trained by backpropagating through only the last k loops. We measure how much of the weight gradient this throws away, exactly and for every k from one backward pass, on nine looped
Stay posted· Newsletter
Three short emails a week: Monday, Wednesday and Friday. Top movers, new models and the most-referenced story.
Your email is used only to send The Bubble Brief. Privacy policy
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivRetrieval Augmented Generation Compositionality7harxivEvolving with Open Worlds: Towards Recursive Self-Improvement for Future Forecasting7harxivTowards English - Mizo Legal Machine Translation: Corpus Creation, Analysis, and Benchmarks7harxivVeriEvolve: Evaluator-First Evolution for Tool-Using Agents7hThe Bubble Brief
MON · WED · FRIRead AI insights every Monday, Wednesday and Friday — top movers, new models, story of the week.
Your email is used only to send The Bubble Brief. Privacy policy
Originally published on arxiv ↗