--- license: mit task_categories: - other tags: - mechanistic-interpretability - robustness - language-model-evaluation - perturbation-analysis --- # Decoding Robustness Results Mechanistic robustness evaluation results for language models under six input perturbations: character replacement, BPE-token replacement, word replacement, local token shuffle, typographical corruption, and synonym replacement. The repository is organized by model and perturbation: ```text models////evals.csv ``` The `qwen2.5_1.5b/adversarial` directory contains the separate adversarial evaluation outputs and manifest. Failed or mislabeled Kaggle runs are not included in the canonical result directories. Recovered model coverage currently includes complete sweeps for GPT-2, GPT-2 Medium, GPT-2 XL, Qwen 2.5 0.5B, and Qwen 2.5 1.5B. GPT-2 Large is represented by a partial legacy run under `models/gpt2-large/`; it contains 11 `char` percentages and 2 valid `token` percentages. An empty GPT-2 Large `token/20` file and an empty legacy GPT-2 XL file were excluded as invalid results. The GPT-2 XL split-A and split-B outputs are merged under `models/gpt2-xl/`. Source dataset: WikiText-2 raw test split (`Salesforce/wikitext`, `wikitext-2-raw-v1`).