OPT

A new arXiv paper (2609.05448v1) formulates structured post-training pruning of vision and language transformers as a damage-aware multi-armed bandit problem under a fixed candidate-evaluation budget,…

A new study from arXiv preprint 2607.24797v1 finds that decoder-only large language models (LLMs) such as GPT-2, OPT, and Pythia entangle reading and writing into a single code, unlike the human brain…

A new paired-minimum detectable effect (MDE) budget for 4-bit quantization benchmarks, derived from classical sample-size calculations, provides benchmark designers a one-line formula to pre-register …