Nina Nusbaumer
@nina-nusbaumer.bsky.social
Sentence processing modeling | Computational psycholinguistics | PhD student at LLF, CNRS, Université Paris Cité | Currently visiting COLT, Universitat Pompeu Fabra, Barcelona, Spain
https://ninanusb.github.io/
https://ninanusb.github.io/
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! 👀
Expected to be released in open-source in the upcoming months. Keep an eye out! 👀
December 19, 2025 at 4:32 PM
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! 👀
Expected to be released in open-source in the upcoming months. Keep an eye out! 👀
Reposted by Nina Nusbaumer
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...
@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...
December 19, 2025 at 4:03 PM
Reposted by Nina Nusbaumer
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
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
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...
arxiv.org
October 15, 2025 at 1:58 PM
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
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
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...
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...
October 2, 2025 at 5:28 PM
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...
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...