About

Code for "Probing for Reading Times".

Environment

# Python 3.11.6
pip install -r requirements.txt

Data

Provo

Download Provo from the Open Science Framework

Preprocess with preprocess_provo.py

Score with score_embed.py

Compute information value with score_infovalue.py and logit lens with score_logitlens.py

Convert to word level with tok2w_provo.py

Tune with tune_reg.py

Cross-validate with provo_crossval.py

MECO

Download MECO from https://github.com/rycolab/context-reading-time/tree/main/merged_data_no_zero

Download the plaintext version of MECO

Score with score_embed.py

Compute information value with score_infovalue.py and logit lens with score_logitlens.py

Convert to word level with tok2w_meco.py

Tune with tune_meco.py

Cross-validate with meco_crossval.py

Hyperparameters

Tuning hyperparameters for all settings can be found here

Note

Stay tuned for recommended folder names and a generally tidier version of the code.

Citation

@inproceedings{tsipidi-etal-2026-probing,
    title = "Probing for Reading Times",
    author = "Tsipidi, Eleftheria  and
      Kiegeland, Samuel  and
      Re, Francesco Ignazio  and
      Xu, Tianyang  and
      Giulianelli, Mario  and
      Stanczak, Karolina  and
      Cotterell, Ryan",
    editor = "Liakata, Maria  and
      Moreira, Viviane P.  and
      Zhang, Jiajun  and
      Jurgens, David",
    booktitle = "Proceedings of the 64th Annual Meeting of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)",
    month = jul,
    year = "2026",
    address = "San Diego, California, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2026.acl-long.575/",
    doi = "10.18653/v1/2026.acl-long.575",
    pages = "12618--12642",
    ISBN = "979-8-89176-390-6"
}