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Nina Nusbaumer

@nina-nusbaumer.bsky.social
61 followers 127 following 3 posts

Computational sentence processing modeling | Computational psycholinguistics | PhD student at LLF, CNRS, Université Paris Cité | Currently visiting COLT, Universitat Pompeu Fabra, Barcelona, Spain ninanusb.github.io

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Nina Nusbaumer @nina-nusbaumer.bsky.social · 22/09/2026
New paper🎉 With Nazanin Shafiabadi & Olivier Bonami, we ask how predictable French noun gender is from form alone. LSTMs (no suffix info given) reach ~90% accuracy and converge exactly on suffix boundaries, suggesting morphology drives this predictability. 🔗 www.peren-revues.fr/lexique/2262
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Reposted by Nina Nusbaumer
Caroline Rowland @carorowland.bsky.social · 27/08/2026
This is the perfect title for the final lecture in the Analytical Connectionism school. www.analytical-connectionism.net/school/2026/
Title slide of a presentation.  Title: Are LLMs relevant from studying language development in humans?
Author: Afra Alishahi
Affiliation: Center for Cognitive Science and AI
Tilburg University, the Netherlands
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Nina Nusbaumer @nina-nusbaumer.bsky.social · 19/12/2025
Presented our new **reading time benchmark for Human Sentence Processing modeling** at the Computational Psycholinguistics Meeting in Utrecht 🧠 Expected to be released in open-source in the upcoming months. Keep an eye out! 👀
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Reposted by Nina Nusbaumer
Marianne de Heer Kloots @mdhk.net · 19/12/2025
Cool posters from day 2! @sashakenjeeva.bsky.social openreview.net/forum?id=Vtd... github.com/markvandenho... openreview.net/forum?id=rX3... @nina-nusbaumer.bsky.social openreview.net/forum?id=GRz... www.ru.nl/personen/sui... openreview.net/forum?id=NcJ...
Poster title: Does multimodal pre-activation influence linguistic expectations in LLMs and humans?

Authors: Sasha Kenjeeva, Giovanni Cassani, Noortje Venhuizen, Afra AlishahiPoster title: Generalizing Without Evidence: How Transformer Models Infer Syntactic Rules From Sparse Input

Authors: Mark van den Hoorn, Raquel G. AlhamaPoster title: Dependency Length, Syntactic Complexity & Memory: A Reading Time Benchmark for Sentence Processing Modeling

Authors: Nina Nusbaumer, Corentin Bel, Iria de-Dios-Flores, Guillaume Wisniewski, Benoit CrabbéPoster title: 
The success of Neural Language Models on syntactic island effects is not universal: strong wh-island sensitivity in English but not in Dutch

Authors: Michelle Suijkerbuijk, Naomi Tachikawa Shapiro, Peter de Swart, Stefan L. Frank
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Reposted by Nina Nusbaumer
Cameron Buckner @cameronbuckner.bsky.social · 15/10/2025
Another banger from @tallinzen.bsky.social . Also fits with some of the criticisms of Centaur and my faculty-based approach generally; if you want LLMs to model human cognition, give them more architecture akin to human faculty psychology like long and short-term memory. arxiv.org/abs/2510.05141
arxiv.org
To model human linguistic prediction, make LLMs less superhuman
When people listen to or read a sentence, they actively make predictions about upcoming words: words that are less predictable are generally read more slowly than predictable ones. The success of larg...
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Nina Nusbaumer @nina-nusbaumer.bsky.social · 02/10/2025
First paper is out! Had so much fun presenting it in Marseille last July 🇨🇵 We explore how transformers handle compositionality by exploring the representations of the idiomatic and literal meaning of the same noun phrase (e.g. "silver spoon"). aclanthology.org/2025.jeptaln...
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