13 citations · 35 across the 23 of their papers we have counts for
28 papers
Not-So-Strange Love: Language Models and Generative Linguistic Theories are More Compatible than They Appear
R. Thomas McCoy
Futrell and Mahowald (2025) frame the success of neural language models (LMs) as supporting gradient, usage-based linguistic theories. I argue that LMs can also instantiate theorie…
You Can't Fight in Here! This is BBS!
Richard Futrell, Kyle Mahowald
Norm, the formal theoretical linguist, and Claudette, the computational language scientist, have a lovely time discussing whether modern language models can inform important questi…
Across the Levels of Analysis: Explaining Predictive Processing in Humans Requires More Than Machine-Estimated Probabilities
Sathvik Nair, Colin Phillips
Under the lens of Marr's levels of analysis, we critique and extend two claims about language models (LMs) and language processing: first, that predicting upcoming linguistic infor…
Are Language Models Models?
Philip Resnik
Futrell and Mahowald claim LMs "serve as model systems", but an assessment at each of Marr's three levels suggests the claim is clearly not true at the implementation level, poorly…
Linguists should learn to love speech-based deep learning models
Marianne de Heer Kloots, Paul Boersma, Willem Zuidema
Futrell and Mahowald present a useful framework bridging technology-oriented deep learning systems and explanation-oriented linguistic theories. Unfortunately, the target article's…
Large language models are not about natural language
Johan J. Bolhuis, Andrea Moro, Stephen Crain +1
Large Language Models are useless for linguistics, as they are probabilistic models that require a vast amount of data to analyse externalized strings of words. In contrast, human…
Language models as tools for investigating the distinction between possible and impossible natural languages
Julie Kallini, Christopher Potts
We argue that language models (LMs) have strong potential as investigative tools for probing the distinction between possible and impossible natural languages and thus uncovering t…
How Linguistics Learned to Stop Worrying and Love the Language Models
Richard Futrell, Kyle Mahowald
Language models can produce fluent, grammatical text. Nonetheless, some maintain that language models don't really learn language and also that, even if they did, that would not be…
Mission: Impossible Language Models
Julie Kallini, Isabel Papadimitriou, Richard Futrell +2
Chomsky and others have very directly claimed that large language models (LLMs) are equally capable of learning languages that are possible and impossible for humans to learn. Howe…
Revisiting the Optimality of Word Lengths
Tiago Pimentel, Clara Meister, Ethan Gotlieb Wilcox +2
Zipf (1935) posited that wordforms are optimized to minimize utterances' communicative costs. Under the assumption that cost is given by an utterance's length, he supported this cl…
Counterfactual Probing for the Influence of Affect and Specificity on Intergroup Bias
Venkata S Govindarajan, Kyle Mahowald, David I. Beaver +1
While existing work on studying bias in NLP focues on negative or pejorative language use, Govindarajan et al. (2023) offer a revised framing of bias in terms of intergroup social…
A Method for Studying Semantic Construal in Grammatical Constructions with Interpretable Contextual Embedding Spaces
Gabriella Chronis, Kyle Mahowald, Katrin Erk
We study semantic construal in grammatical constructions using large language models. First, we project contextual word embeddings into three interpretable semantic spaces, each de…
Analogy in Contact: Modeling Maltese Plural Inflection
Sara Court, Andrea D. Sims, Micha Elsner
Maltese is often described as having a hybrid morphological system resulting from extensive contact between Semitic and Romance language varieties. Such a designation reflects an e…
Elaborative Simplification as Implicit Questions Under Discussion
Yating Wu, William Sheffield, Kyle Mahowald +1
Automated text simplification, a technique useful for making text more accessible to people such as children and emergent bilinguals, is often thought of as a monolingual translati…
A Discerning Several Thousand Judgments: GPT-3 Rates the Article + Adjective + Numeral + Noun Construction
Kyle Mahowald
Knowledge of syntax includes knowledge of rare, idiosyncratic constructions. LLMs must overcome frequency biases in order to master such constructions. In this study, I prompt GPT-…
For Generated Text, Is NLI-Neutral Text the Best Text?
Michail Mersinias, Kyle Mahowald
We explore incorporating natural language inference (NLI) into the text generative pipeline by using a pre-trained NLI model to assess whether a generated sentence entails, contrad…
Why is Winoground Hard? Investigating Failures in Visuolinguistic Compositionality
Anuj Diwan, Layne Berry, Eunsol Choi +2
Recent visuolinguistic pre-trained models show promising progress on various end tasks such as image retrieval and video captioning. Yet, they fail miserably on the recently propos…
Inducing Character-level Structure in Subword-based Language Models with Type-level Interchange Intervention Training
Jing Huang, Zhengxuan Wu, Kyle Mahowald +1
Language tasks involving character-level manipulations (e.g., spelling corrections, arithmetic operations, word games) are challenging for models operating on subword units. To add…
longhorns at DADC 2022: How many linguists does it take to fool a Question Answering model? A systematic approach to adversarial attacks
Venelin Kovatchev, Trina Chatterjee, Venkata S Govindarajan +9
Developing methods to adversarially challenge NLP systems is a promising avenue for improving both model performance and interpretability. Here, we describe the approach of the tea…
What do tokens know about their characters and how do they know it?
Ayush Kaushal, Kyle Mahowald
Pre-trained language models (PLMs) that use subword tokenization schemes can succeed at a variety of language tasks that require character-level information, despite lacking explic…
When classifying grammatical role, BERT doesn't care about word order... except when it matters
Isabel Papadimitriou, Richard Futrell, Kyle Mahowald
Because meaning can often be inferred from lexical semantics alone, word order is often a redundant cue in natural language. For example, the words chopped, chef, and onion are mor…
Grammatical cues to subjecthood are redundant in a majority of simple clauses across languages
Kyle Mahowald, Evgeniia Diachek, Edward Gibson +2
Grammatical cues are sometimes redundant with word meanings in natural language. For instance, English word order rules constrain the word order of a sentence like "The dog chewed…
A Massively Multilingual Analysis of Cross-linguality in Shared Embedding Space
Alex Jones, William Yang Wang, Kyle Mahowald
In cross-lingual language models, representations for many different languages live in the same space. Here, we investigate the linguistic and non-linguistic factors affecting sent…
How (Non-)Optimal is the Lexicon?
Tiago Pimentel, Irene Nikkarinen, Kyle Mahowald +2
The mapping of lexical meanings to wordforms is a major feature of natural languages. While usage pressures might assign short words to frequent meanings (Zipf's law of abbreviatio…