A unified interface for computing surprisal (log probabilities) from language models! Supports neural, symbolic, and black-box API models.
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Updated
Mar 20, 2026 - Python
A unified interface for computing surprisal (log probabilities) from language models! Supports neural, symbolic, and black-box API models.
A playful experiment turning LLM surprisal values into musical melodies (and vice versa)
Jupyter notebooks on Google Colab to calculate surprisal for experimental stimuli, using the minicons package.
On the Proper Treatment of Units in Surprisal Theory - code for computing surprisal over arbitrary unit inventories from language models (ACL 2026)
Reverse-Engineering the Reader - code for aligning language models to human psychometric data (EMNLP 2024).
Quantifying surprise in clinical care
Quantifying surprise in clinical care
The C-SALT-mix corpus and analysis for the Open Mind paper 'Signal Smoothing and Syntactic Choices: A Critical Reflection on the UID Hypothesis' (MIT Press).
Открыл секрет стихотворения "Жди меня" https://dzen.ru/video/watch/69426bca41a09c78095e98d2
ALSI/ILSA is a lexical and syntactic analyzer
Reproducible real-EEG workbench for exact language-model surprisal, human N400 effects, held-out alignment, and causal auditing.
Multilingual toolkit for evaluating LLMs using embeddings
Research code for testing whether causal token surprisal can guide adaptive computation, sparse refinement, and learned compute allocation in byte-level language models.
This repository is for the paper Word Surprisal Correlates with Sentential Contradiction in LLMs. In Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers), pages 4549–4564, Rabat, Morocco. Association for Computational Linguistics.
Interactive GPT-2 surprisal calculator - AI-assisted development demo
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