Tal Linzen

Professor and Researcher in Linguistics and Data Science

New York

About

Tal Linzen is an Associate Professor of Linguistics and Data Science at New York University and a Research Scientist at Google. Before moving to NYU in 2020, he was a faculty member at Johns Hopkins University, and before that, a postdoctoral researcher at the École Normale Supérieure in Paris. He received his PhD from NYU in 2015. At NYU, he directs the Computation and Psycholinguistics (CAP) Lab, which studies the connections between machine learning and human language comprehension and acquisition, with a particular focus on understanding and mimicking humans’ ability to learn quickly and generalize effectively. As part of this enterprise, the CAP lab develops novel evaluation and analysis techniques for neural network models, drawing inspiration from linguistics and cognitive science. He has received a Google Faculty Award and a National Science Foundation CAREER award.

Publications

Prompt2DAG: A Modular LLM-Prompting Methodology for Data Enrichment Pipeline Generation
Unknown Venue
2025
Learning to Learn to Disambiguate: Meta-Learning for Few-Shot Word Sense Disambiguation
Findings of the Association for Computational Linguistics: EMNLP 2020
2020
Learning filler-gap dependencies with neural language models: Testing island sensitivity in Norwegian and English
Journal of Memory and Language
2025
Between Circuits and Chomsky: Pre-pretraining on Formal Languages Imparts Linguistic Biases
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
2025
What Goes Into a LM Acceptability Judgment? Rethinking the Impact of Frequency and Length
Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
2025
Bigger is not always better: The importance of human-scale language modeling for psycholinguistics
Unknown Venue
2025
How does the task complexity of masked pretraining objectives affect downstream performance?
Findings of the Association for Computational Linguistics: ACL 2023
2023
A Systematic Comparison of Syllogistic Reasoning in Humans and Language Models
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
2024
SPAWNing Structural Priming Predictions from a Cognitively Motivated Parser
Proceedings of the 28th Conference on Computational Natural Language Learning
2024
Can You Learn Semantics Through Next-Word Prediction? The Case of Entailment
Findings of the Association for Computational Linguistics ACL 2024
2024
Parsing Ambiguity in Mandarin Chinese: Garden Path Effects Induced by the Functional Particle "的" (DE)
2025 International Conference on Asian Language Processing (IALP)
2025
In-context Learning Generalizes, But Not Always Robustly: The Case of Syntax
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
2024
The Impact of Depth on Compositional Generalization in Transformer Language Models
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
2024
Do Language Models’ Words Refer?
Computational Linguistics
2024
Neural Networks as Cognitive Models of the Processing of Syntactic Constraints
Open Mind
2024
Large-scale benchmark yields no evidence that language model surprisal explains syntactic disambiguation difficulty
Journal of Memory and Language
2024
A Language Model with Limited Memory Capacity Captures Interference in Human Sentence Processing
Findings of the Association for Computational Linguistics: EMNLP 2023
2023
SLOG: A Structural Generalization Benchmark for Semantic Parsing
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
2023
Verb Conjugation in Transformers Is Determined by Linear Encodings of Subject Number
Findings of the Association for Computational Linguistics: EMNLP 2023
2023
How poor is the stimulus? Evaluating hierarchical generalization in neural networks trained on child-directed speech
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
2023
How to Plant Trees in Language Models: Data and Architectural Effects on the Emergence of Syntactic Inductive Biases
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
2023
Neural Networks Can Learn Patterns of Island-insensitivity in Norwegian
Unknown Venue
2023
How Much Do Language Models Copy From Their Training Data? Evaluating Linguistic Novelty in Text Generation Using RAVEN
Transactions of the Association for Computational Linguistics
2023
Characterizing Verbatim Short-Term Memory in Neural Language Models
Proceedings of the 26th Conference on Computational Natural Language Learning (CoNLL)
2022
Syntactic Surprisal From Neural Models Predicts, But Underestimates, Human Processing Difficulty From Syntactic Ambiguities
Proceedings of the 26th Conference on Computational Natural Language Learning (CoNLL)
2022
Causal Analysis of Syntactic Agreement Neurons in Multilingual Language Models
Proceedings of the 26th Conference on Computational Natural Language Learning (CoNLL)
2022
Entailment Semantics Can Be Extracted from an Ideal Language Model
Proceedings of the 26th Conference on Computational Natural Language Learning (CoNLL)
2022
LSTMs Can Learn Basic Wh- and Relative Clause Dependencies in Norwegian
Unknown Venue
2022
Improving Compositional Generalization with Latent Structure and Data Augmentation
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
2022
When a sentence does not introduce a discourse entity, Transformer-based models still sometimes refer to it
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
2022
Coloring the Blank Slate: Pre-training Imparts a Hierarchical Inductive Bias to Sequence-to-sequence Models
Findings of the Association for Computational Linguistics: ACL 2022
2022
Self-Adaptive Logit Balancing for Deep Learning Robustness in Computer Vision
Lecture Notes in Computer Science
2022
Evaluating Attribution in Dialogue Systems: The BEGIN Benchmark
Transactions of the Association for Computational Linguistics
2022
Rapid syntactic adaptation in self-paced reading: Detectable, but only with many participants.
Journal of Experimental Psychology: Learning, Memory, and Cognition
2021
Single‐Stage Prediction Models Do Not Explain the Magnitude of Syntactic Disambiguation Difficulty
Cognitive Science
2021
Syntactic Structure from Deep Learning
Annual Review of Linguistics
2021
The Language Model Understood the Prompt was Ambiguous: Probing Syntactic Uncertainty Through Generation
Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP
2021
Does Putting a Linguist in the Loop Improve NLU Data Collection?
Findings of the Association for Computational Linguistics: EMNLP 2021
2021
NOPE: A Corpus of Naturally-Occurring Presuppositions in English
Proceedings of the 25th Conference on Computational Natural Language Learning
2021
Counterfactual Interventions Reveal the Causal Effect of Relative Clause Representations on Agreement Prediction
Proceedings of the 25th Conference on Computational Natural Language Learning
2021
Causal Analysis of Syntactic Agreement Mechanisms in Neural Language Models
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
2021
LMPred: Predicting Antimicrobial Peptides Using Pre-Trained Language Models and Deep Learning
Unknown Venue
2021
Priming syntactic ambiguity resolution in children and adults
Language, Cognition and Neuroscience
2020
Does Syntax Need to Grow on Trees? Sources of Hierarchical Inductive Bias in Sequence-to-Sequence Networks
Transactions of the Association for Computational Linguistics
2020
COGS: A Compositional Generalization Challenge Based on Semantic Interpretation
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
2020
Discovering the Compositional Structure of Vector Representations with Role Learning Networks
Proceedings of the Third BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP
2020
BERTs of a feather do not generalize together: Large variability in generalization across models with similar test set performance
Proceedings of the Third BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP
2020
Cognitive Biases, Linguistic Universals, and Constraint‐Based Grammar Learning
Topics in Cognitive Science
2013
Neural Language Models Capture Some, But Not All, Agreement Attraction Effects
Unknown Venue
2020
Cross-Linguistic Syntactic Evaluation of Word Prediction Models
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
2020
How Can We Accelerate Progress Towards Human-like Linguistic Generalization?
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
2020
Representations of Syntax [MASK] Useful: Effects of Constituency and Dependency Structure in Recursive LSTMs
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
2020
Syntactic Data Augmentation Increases Robustness to Inference Heuristics
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
2020
Yet Again on the Russian Genitive of Negation: Another Perspective
Russian Linguistics
2003
Analyzing and interpreting neural networks for NLP: A report on the first BlackboxNLP workshop
Natural Language Engineering
2019
Using Priming to Uncover the Organization of Syntactic Representations in Neural Language Models
Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)
2019
Quantity doesn’t buy quality syntax with neural language models
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
2019
Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inference
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
2019
Learning to Sort: Few-shot Spike Sorting with Adversarial Representation Learning
2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
2019
Probing What Different NLP Tasks Teach Machines about Function Word Comprehension
Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019)
2019
Studying the Inductive Biases of
Proceedings of the 2019 Conference of the North
2019
Neural network surprisal predicts the existence but not the magnitude of human syntactic disambiguation difficulty
Unknown Venue
2019
What can linguistics and deep learning contribute to each other? Response to Pater
Language
2019
The reliability of acceptability judgments across languages
Glossa: a journal of general linguistics
2018
In spoken word recognition the future predicts the past
Unknown Venue
2017
A Neural Model of Adaptation in Reading
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
2018
Targeted Syntactic Evaluation of Language Models
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
2018
Learning Syntactic Frames with Simple Recurrent Networks
Proceedings of the Twentieth Annual Conference of the Cognitive Science Society
2022
Colorless Green Recurrent Networks Dream Hierarchically
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)
2018
Phonological (un)certainty weights lexical activation
Proceedings of the 8th Workshop on Cognitive Modeling and Computational Linguistics (CMCL 2018)
2018
The role of linguistic schools in language teaching
Zamonaviy lingvistik tadqiqotlar: xorijiy tajribalar, istiqbolli izlanishlar va tillarni o‘qitishning innovatsion usullari
2022
Symbolic Inductive Bias for Visually Grounded Learning of Spoken Language
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
2019
Rapid generalization in phonotactic learning
Laboratory Phonology: Journal of the Association for Laboratory Phonology
2017
Exploring the Syntactic Abilities of RNNs with Multi-task Learning
Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017)
2017
What Determines Visual Statistical Learning Performance? Insights From Information Theory
Cognitive Science
2019
Comparing Character-level Neural Language Models Using a Lexical Decision Task
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers
2017
Assessing the Ability of LSTMs to Learn Syntax-Sensitive Dependencies
Transactions of the Association for Computational Linguistics
2016
Against all odds: exhaustive activation in lexical access of verb complementation options
Language, Cognition and Neuroscience
2016
The diminishing role of inalienability in the Hebrew possessive dative
Corpus Linguistics and Linguistic Theory
2016
Uncertainty and Expectation in Sentence Processing: Evidence From Subcategorization Distributions
Cognitive Science
2015
Issues in evaluating semantic spaces using word analogies
Proceedings of the 1st Workshop on Evaluating Vector-Space Representations for NLP
2016
Evaluating vector space models using human semantic priming results
Proceedings of the 1st Workshop on Evaluating Vector-Space Representations for NLP
2016
Quantificational features in distributional word representations
Proceedings of the Fifth Joint Conference on Lexical and Computational Semantics
2016
Lexical Preactivation in Basic Linguistic Phrases
Journal of Cognitive Neuroscience
2015
Morphological conditioning of phonological regularization
The Linguistic Review
2015
A model of rapid phonotactic generalization
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing
2015
Pronominal datives
Studies in Language
2015
Parallels between cross-linguistic and language-internal variation in Hebrew possessive constructions
Linguistics
2014
The role of morphology in phoneme prediction: Evidence from MEG
Brain and Language
2014
Investigating the role of entropy in sentence processing
Proceedings of the Fifth Workshop on Cognitive Modeling and Computational Linguistics
2014
The Timecourse of Generalization in Phonotactic Learning
Proceedings of the Annual Meetings on Phonology
2014
Syntactic context effects in visual word recognition
The Mental Lexicon
2013
Lexical and phonological variation in Russian prepositions
Phonology
2013

Education

New York University

Ph.D. / 2015

Tel Aviv University

M.A. / 2010

Tel Aviv University

B.Sc. / 2010

Tel Aviv University

B.Sc. / 2010

Experience

New York University

Associate Professor / January, 2023 — January

Department of Linguistics and Center for Data Science

Assistant Professor / January, 2020 — January, 2023

Department of Linguistics and Center for Data Science

Google

Research Scientist / January, 2021 — January, 2021

(Projects focus on language model post-training evaluation and interpretability)

Johns Hopkins University

Assistant Professor / January, 2017 — January, 2020

Department of Cognitive Science (primary appointment) Department of Computer Science (joint appointment) Affiliated faculty Center for Language and Speech Processing

Laboratoire de Sciences Cognitives et Psycholinguistique Institut Jean Nicod Ecole Normale Suprieure Paris

Postdoctoral researcher / January, 2015 — January, 2017

None

Links & Social Media

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