We are pleased to welcome the following keynote speakers to WoProc 2026 in Lisbon:
– Davide Crepaldi (University of Pavia) @CrepaldiDavide
– Jana Reifegerste (Georgetown University) @schnuffichen
https://t.co/QBJGRVWQDp
Abstract submission by 14 Feb!📢
We will also hold ...
... and a two-day post-conference workshop on 9–10 July on "Bayesian statistics for word processing research".
This is directed at early-career researchers, and free to attend for conference participants!
We are pleased to welcome the following keynote speakers to WoProc 2026 in Lisbon:
– Davide Crepaldi (University of Pavia) @CrepaldiDavide
– Jana Reifegerste (Georgetown University) @schnuffichen
https://t.co/QBJGRVWQDp
Abstract submission by 14 Feb!📢
We will also hold ...
… an invited symposium on "Emerging computational approaches to lexicon and morphology", with:
– Sol Lago (Goethe University Frankfurt) @sol_lago
– Evelina Leivada (Universitat Autònoma de Barcelona) @EvelinaLeivada
– Marco Marelli (University of Milano-Bicocca)
Final call for papers!📢
Deadline extended to 14 February 2026!
Join us in Lisbon next year for the International Word Processing Conference, on 6–8 July 2026. We welcome contributions on all aspects of word processing. https://t.co/jVt3YNHbc5
New book! I have written a book, called Syntax: A cognitive approach, published by MIT Press.
This is open access; MIT Press will post a link soon, but until then, the book is available on my website:
https://t.co/ksQfTGoxpK
A paper with Vic Ferreira and Norvin Richards is now out in JML!
(1) Speakers syntactically encode zero complementizers as cognitively active mental object.
(2) No evidence LLMs capture cross constructional generalizations about zero complementizers.
https://t.co/ELU1VyOhSE
We welcome contributions on all aspects of word processing (submit by 23 Jan 2026)!
Very happy to announce these two fantastic keynotes:
- Davide Crepaldi @CrepaldiDavide
- Jana Reifegerste @schnuffichen
SAVE THE DATE! Join us in Lisbon next year for the International Word Processing Conference (6–8 July 2026)!
WoProc continues the legacy of MoProc―a conference that, since 1999, has brought together researchers working on morphological processing.
https://t.co/qaw3BE0j0F
Next week onwards, I'm teaching a five-day introductory course on Bayesian Data Analysis in Gent. Newly recorded video lectures to accompany the course are now online: https://t.co/fO6Z6becsK
Our new article with @jgeller_phd, Julia Drouin & @SarahColby12 on webcam eye tracking is out now!
🔗 https://t.co/Maft8evPfA
⭐️All materials are open access, and you’ll get code to analyze your @GorillaPsyc eye tracking data in no time! (Free full-text for 50 days!)
Very excited to publicly share news about a new tool, Papercheck, that Lisa DeBruine and me started to develop more than a year ago! In an introductory blog post, we explain our philosophy to automatically check scientific papers for best practices. https://t.co/yJH8w0AAEm
Instead, better tone identification was predicted by pitch acuity. This suggests that domain-general auditory processing―not universal phonological principles―is a more important determinant.
New paper with Chao Zhou in BLC: https://t.co/lmTH3HpmwT
What makes lexical tones challenging for L2 learners? Previous studies suggest that phonological universals are at play... In our perceptual study, we found little evidence for these universals.
How do memory retrieval and prediction work together during sentence comprehension?
We use computational modeling + eye-tracking to unpack their interaction in German possessive pronouns. New paper with @_joaoverissimo, @_mesh and @sol_lago https://t.co/poupJ5OmQ3
🤯📈 TAKE YOUR STATS SKILLZ TO THE NEXT LEVEL WITH THIS #R PACKAGE
🔥The @easystats4u {modelbased} package (the successor of #ggeffects) is now published in @JOSS_TheOJ
https://t.co/A897NTJMzZ
Check it out for a demystification of marginal means, contrasts and effects #rlang
It's an intro to the foundational principles of Bayesian stats AND a practical tutorial on estimation and hypothesis testing using brms. I build up from simple regression to mixed-effects models.
Very interesting paper on causal inference from statistical models; perhaps more actionable than most causal inference papers:
https://t.co/0JnAYMNCMK #Statistics