The paper introduces Brittlebench, a framework and evaluation pipeline that measures how sensitive large language models (LLMs) are to prompt variations. By applying semantics‑preserving perturbations to popular benchmarks, the authors show that model performance can drop by up to 12% and that such perturbations can change model rankings in 63% of cases. The study finds that these input variations can explain up to half of the performance variance for a given model, underscoring the importance of robust evaluation methods.
By Angelika Romanou, Mark Ibrahim, Candace Ross, Kerem Oktar, Chantal Shaib, Samuel J. Bell, Anaelia Ovalle, Antoine Bosselut, Jesse Dodge, Koustuv Sinha, Adina Williams
arXiv:2608. 03983v1 Announce Type: cross Abstract: Optimizing compilers miss profitable transformations when their enabling semantics are absent from the analyzed program representation.
By Hailong Jiang, Feng Yu, Emran Hossain, Jianfeng Zhu, Mengfei Ren, Qiang Guan, Chunwei Xia
arXiv:2608. 08700v1 Announce Type: new Abstract: Reliable evaluation of tool routing is critical as Large Language Models increasingly operate as autonomous agents.
By Dongjie Xu, Julius, Hanchi Dong, Minghua Tang, Yuxuan Sun, Ziwei Nie, Zicheng Liu, Dujun Qing, Jiajie Xu
arXiv:2607. 18642v1 Announce Type: new Abstract: Mined code corpora are abundant but uncontrolled: a snippet's semantics, surface "messiness," and difficulty are whatever the wild contained; there is no known-optimal reference to grade against; and any public sample may already sit in a model's training set.
By Yuxiang Ji
AI code agents are increasingly deployed to resolve real software issues, yet their reliability under superficial code variations remains poorly understood. We evaluate whether coding agents that repa...
arXiv:2610.07070v1 Announce Type: new
Abstract: Small language models are inexpensive to serve and can run on private infrastructure, but base models are often not good enough at multi-turn tool call...
By Aaron Fainman, Gabriela Kadlecov\'a, Maciej Gryka, Bartosz Kruszczy\'nski, Usman Zafar, C\'edric Archambeau, Aaron Klein, David Salinas, Selim Nowicki, Jacek Golebiowski