ai-ml

Weekly Paper Notes — one of the top picks from the May 24–30, 2026 CS paper digest. Area: AI / ML. Authors: Lukas Aichberger, Sepp Hochreiter (JKU Linz / NXAI) arXiv: 2605.30343 · PDF TL;DR Modern reasoning LLMs scale test-time compute by emitting long chains of thought — but every “thought token” is forced to round-trip through the autoregressive decoder, conflating internal computation with external communication. Reasoning in Memory (RiM) instead inserts blocks of fixed special tokens that act as scratch space for the model’s working memory....

Weekly Paper Notes — one of the top picks from the May 17–23, 2026 CS paper digest. Area: AI / ML. Authors: Ali Hatamizadeh, Yejin Choi, Jan Kautz (NVIDIA) arXiv: 2605.22791 · PDF · Code TL;DR Linear-attention models compress an unbounded history into a fixed-size recurrent state, but their active edit — the operation that overwrites stale associations with new ones — has historically been controlled by a single scalar gate that decides both how much old content to erase and how much new content to write....