Revising with a Backward Glance

This repository accompanies the publication:

Revising with a Backward Glance: Regressions and Skips during Reading as Cognitive Signals for Revision Policies in Incremental Processing.

by Brielen Madureira, Pelin Çelikkol and David Schlangen at CoNLL 2023.

Set Up

1. Create the preprocessed directory structure. Commands are in the first block of setup.sh.
2. Create the Python environment. The steps we used are in setup.sh. Alternatively, install via conda or pip using environment.yml and requirements.txt, repectively.
3. Download the data. Follow the instructions in data/README.md.

Data Preprocessing

1. Extract human regressions and number of fixations. Run the preprocess_human_data.ipynb notebook. Human data will be saved into preprocessed/human_data.
2. Extract models outputs, revisions and edits. Run the preprocess_model_data.ipynb notebook. Models data will be saved into preprocessed/model_data and preprocessed/model_outputs.
3. Merge the files. Run the merge_data.ipynb notebook.

Data preprocessing for models, humans and merge run on June 27, 2023.

Analysis

1. Run the R scripts for the analysis. Results should be saved into results/.
2. Create plots and tables. Run the plots-tables.ipynb notebook.