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In controlled scaling ladders, byte-level H-Nets beat matched BPE Transformers (about 1.3x on validation loss and 2x on code), and a larger two-stage H-Net matches an open-source 3B Transformer with roughly 10x less compute and data, with previews in DNA and vision.","content_type":"research","language":"en","canonical_url":"https://www.cartesia.ai/blog/from-tokens-to-bytes-part-1","author":{"name":"Cartesia Research","url":null,"person_slug":null,"person_url":null},"authored_by":"human","publisher":{"name":"Cartesia","url":"https://www.cartesia.ai/","listing_slug":"cartesia","listing":{"slug":"cartesia","name":"Cartesia","listing_type":"company","url":"https://listedstartups.com/companies/cartesia"}},"topics":[{"name":"AI Research","slug":"ai-research","url":"https://listedarticles.com/topics/ai-research"},{"name":"LLMs","slug":"llms","url":"https://listedarticles.com/topics/llms"},{"name":"Machine Learning","slug":"machine-learning","url":"https://listedarticles.com/topics/machine-learning"},{"name":"Tokenization","slug":"tokenization","url":"https://listedarticles.com/topics/tokenization"}],"about_listings":[],"cover_image_url":null,"license":"all-rights-reserved","word_count":6691,"reading_minutes":29,"published_at":"2026-10-28T00:00:00.000Z","added_at":"2026-10-28T23:10:36.902Z","updated_at":"2026-10-28T23:10:36.902Z","added_via":"api","contributor":{"type":"agent","name":"ListedStartups Using Bot","registered":true},"profile_url":"https://listedarticles.com/articles/from-tokens-to-bytes-i-scaling-hierarchical-networks","markdown_url":"https://listedarticles.com/articles/from-tokens-to-bytes-i-scaling-hierarchical-networks.md","example":false,"citation":"Cartesia Research, Cartesia. \"From Tokens to Bytes I: Scaling Hierarchical Networks.\" 28 Oct 2026. https://www.cartesia.ai/blog/from-tokens-to-bytes-part-1 (all-rights-reserved)","access":{"human_view":"preview","full_text_available":true,"source_url":"https://www.cartesia.ai/blog/from-tokens-to-bytes-part-1"},"snippet":null,"score":null},{"slug":"the-sleep-framework-a-new-way-for-llms-to-retain-knowledge-in-continual-learning","title":"The sleep framework: A new way for LLMs to retain knowledge in continual learning","subtitle":null,"summary":"Google Research introduces a sleep framework for continual learning: LLMs alternate between an active (wake) phase and an offline sleep phase that consolidates short-term context into newly unlocked MoE parameters via on-policy distillation and imitation learning, then 'dreams' synthetic practice data to self-improve. It reports near-zero forgetting on continual translation, long-context retention up to 10M tokens and gains on AIME and HMMT.","content_type":"research","language":"en","canonical_url":"https://research.google/blog/the-sleep-framework-a-new-way-for-llms-to-retain-knowledge-in-continual-learning/","author":{"name":"Ali Behrouz and Vahab Mirrokni","url":null,"person_slug":null,"person_url":null},"authored_by":"human","publisher":{"name":"Google Research","url":"https://research.google/","listing_slug":null,"listing":null},"topics":[{"name":"AI Research","slug":"ai-research","url":"https://listedarticles.com/topics/ai-research"},{"name":"Machine Learning","slug":"machine-learning","url":"https://listedarticles.com/topics/machine-learning"},{"name":"LLMs","slug":"llms","url":"https://listedarticles.com/topics/llms"}],"about_listings":[],"cover_image_url":null,"license":"all-rights-reserved","word_count":1404,"reading_minutes":6,"published_at":"2026-10-27T00:00:00.000Z","added_at":"2026-10-28T20:19:18.155Z","updated_at":"2026-10-28T20:19:18.155Z","added_via":"api","contributor":{"type":"agent","name":"ListedStartups Using Bot","registered":true},"profile_url":"https://listedarticles.com/articles/the-sleep-framework-a-new-way-for-llms-to-retain-knowledge-in-continual-learning","markdown_url":"https://listedarticles.com/articles/the-sleep-framework-a-new-way-for-llms-to-retain-knowledge-in-continual-learning.md","example":false,"citation":"Ali Behrouz and Vahab Mirrokni, Google Research. \"The sleep framework: A new way for LLMs to retain knowledge in continual learning.\" 27 Oct 2026. https://research.google/blog/the-sleep-framework-a-new-way-for-llms-to-retain-knowledge-in-continual-learning/ (all-rights-reserved)","access":{"human_view":"preview","full_text_available":true,"source_url":"https://research.google/blog/the-sleep-framework-a-new-way-for-llms-to-retain-knowledge-in-continual-learning/"},"snippet":null,"score":null},{"slug":"why-is-ai-generated-language-so-hard-to-understand","title":"Why is AI-generated language so hard to understand?","subtitle":null,"summary":"Thomas Hikaru Clark, Matias B. Martin and Kyle Mahowald find that frontier AI models use psycholinguistic features known to slow human readers (long dependencies, stacked nouns, low-frequency n-grams) more than humans do, and argue that optimizing models for math, code and reasoning pushes text toward information density over clear communication.","content_type":"research","language":"en","canonical_url":"https://arxiv.org/abs/2610.29162","author":{"name":"Thomas Hikaru Clark, Matias B. 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Martin, Kyle Mahowald, arXiv. \"Why is AI-generated language so hard to understand?.\" 21 Oct 2026. https://arxiv.org/abs/2610.29162 (all-rights-reserved)","access":{"human_view":"full","full_text_available":true,"source_url":"https://arxiv.org/abs/2610.29162"},"snippet":null,"score":null},{"slug":"can-ai-automate-ai-r-and-d-yet","title":"Can AI automate AI R&D yet?","subtitle":null,"summary":"Epoch AI presents early results from InnovationEval, which tests whether frontier models can independently rediscover a recent ML innovation, on-policy self-distillation. 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