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)

Calculate surprisal for words in text.

Jupyter notebooks on Google Colab to calculate surprisal for experimental stimuli, using the minicons package.

Quantifying surprise in clinical care

Quantifying surprise in clinical care

Evaluating syntactic comprehension of large language models on garden-path sentences by comparing computational parsing behaviors against human cognitive patterns.

Using NLP to generate an index for my blog.

Multilingual toolkit for evaluating LLMs using embeddings