6 papers
Estimating Surprisal from the Speech Signal
Zachary Hopton, Samuel Kiegeland, Francesco Ignazio Re +4
Although language is predominantly spoken, empirical tests of surprisal theory rely almost entirely on written text. In practice, surprisal is estimated using language models (LMs)…
Revisiting the Estimation of Unigram Surprisal in Computational Psycholinguistics
Zachary Hopton, Francesco Ignazio Re, Samuel Kiegeland +3
Contextual and unigram surprisal are standard predictors of reading time in computational psycholinguistics. While contextual surprisal is typically derived from neural language mo…
Probing for Reading Times
Eleftheria Tsipidi, Samuel Kiegeland, Francesco Ignazio Re +4
Probing has shown that language model representations encode rich linguistic information, but it remains unclear whether they also capture cognitive signals about human processing.…
A Spatio-Temporal Point Process for Fine-Grained Modeling of Reading Behavior
Francesco Ignazio Re, Andreas Opedal, Glib Manaiev +2
Reading is a process that unfolds across space and time, alternating between fixations where a reader focuses on a specific point in space, and saccades where a reader rapidly shif…
The Harmonic Structure of Information Contours
Eleftheria Tsipidi, Samuel Kiegeland, Franz Nowak +5
The uniform information density (UID) hypothesis proposes that speakers aim to distribute information evenly throughout a text, balancing production effort and listener comprehensi…
BabyLM Turns 3: Call for papers for the 2025 BabyLM workshop
Lucas Charpentier, Leshem Choshen, Ryan Cotterell +11
BabyLM aims to dissolve the boundaries between cognitive modeling and language modeling. We call for both workshop papers and for researchers to join the 3rd BabyLM competition. As…