weekly-papers-2026-07-11

Weekly Paper Notes — one of the top picks from the 2026-07-11 CS paper digest. Area: AI / ML. Authors: Shreyas Subramanian, Adewale Akinfaderin, Akarsha Sehwag (Amazon) arXiv: 2607.08733 · PDF TL;DR “Super Weights” — individual scalar parameters in a large language model whose removal collapses task accuracy — were the interpretability finding of 2024–2025. The natural inference was that if these coordinates matter that much for the forward pass, they should also matter that much for learning: freeze everything else, train only the Super Weights (or a small neighbourhood around them), and you should get parameter-efficient fine-tuning for essentially free....

Weekly Paper Notes — Seminal Paper of the Week for the 2026-07-11 CS paper digest. Area: Distributed Computing / Coordination. Author: Mike Burrows (Google) Venue: OSDI ‘06 — The Chubby lock service for loosely-coupled distributed systems Canonical link: OSDI ‘06 proceedings · PDF Why the paper still matters Twenty years after publication, Chubby is the paper you can point at to explain almost every coordination system in the modern datacenter....

Weekly Paper Notes — one of the top picks from the 2026-07-11 CS paper digest. Area: Distributed Computing / Systems. Authors: Hannah Atmer, Thiemo Voigt, Yuan Yao, Stefanos Kaxiras (Uppsala University) arXiv: 2607.08407 · PDF TL;DR DRAM is the choke point of the current generative-AI buildout. HBM3e stacks are backordered, contract prices are up, and hyperscalers are absorbing a large fraction of global DRAM output just to fan the same model weights out to ever more accelerators....