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cs.CL2023

Exploring Linguistic Probes for Morphological Generalization

Jordan Kodner, Salam Khalifa, Sarah Payne

Modern work on the cross-linguistic computational modeling of morphological inflection has typically employed language-independent data splitting algorithms. In this paper, we supp…

cs.CL20238 cited

Why Linguistics Will Thrive in the 21st Century: A Reply to Piantadosi (2023)

Jordan Kodner, Sarah Payne, Jeffrey Heinz

We present a critical assessment of Piantadosi's (2023) claim that "Modern language models refute Chomsky's approach to language," focusing on four main points. First, despite the…

cs.CL2023

Morphological Inflection: A Reality Check

Jordan Kodner, Sarah Payne, Salam Khalifa +1

Morphological inflection is a popular task in sub-word NLP with both practical and cognitive applications. For years now, state-of-the-art systems have reported high, but also high…

cs.CL2021

The Greedy and Recursive Search for Morphological Productivity

Caleb Belth, Sarah Payne, Deniz Beser +2

As children acquire the knowledge of their language's morphology, they invariably discover the productive processes that can generalize to new words. Morphological learning is made…

cs.CL2021

A Grounded Approach to Modeling Generic Knowledge Acquisition

Deniz Beser, Joe Cecil, Marjorie Freedman +4

We introduce and implement a cognitively plausible model for learning from generic language, statements that express generalizations about members of a category and are an importan…

cs.CL2021

ADAM: A Sandbox for Implementing Language Learning

Ryan Gabbard, Deniz Beser, Jacob Lichtefeld +5

We present ADAM, a software system for designing and running child language learning experiments in Python. The system uses a virtual world to simulate a grounded language acquisit…