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05/26/2023
Counterfactual reasoning: Testing language models' understanding of hypothetical scenarios
Current pre-trained language models have enabled remarkable improvements...
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12/06/2022
Counterfactual reasoning: Do language models need world knowledge for causal understanding?
Current pre-trained language models have enabled remarkable improvements...
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10/05/2022
"No, they did not": Dialogue response dynamics in pre-trained language models
A critical component of competence in language is being able to identify...
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10/05/2022
COMPS: Conceptual Minimal Pair Sentences for testing Property Knowledge and Inheritance in Pre-trained Language Models
A characteristic feature of human semantic memory is its ability to not ...
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05/13/2022
A Property Induction Framework for Neural Language Models
To what extent can experience from language contribute to our conceptual...
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11/12/2021
Variation and generality in encoding of syntactic anomaly information in sentence embeddings
While sentence anomalies have been applied periodically for testing in N...
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09/27/2021
Pragmatic competence of pre-trained language models through the lens of discourse connectives
As pre-trained language models (LMs) continue to dominate NLP, it is inc...
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09/25/2021
Sorting through the noise: Testing robustness of information processing in pre-trained language models
Pre-trained LMs have shown impressive performance on downstream NLP task...
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05/31/2021
On the Interplay Between Fine-tuning and Composition in Transformers
Pre-trained transformer language models have shown remarkable performanc...
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05/06/2021
Do language models learn typicality judgments from text?
Building on research arguing for the possibility of conceptual and categ...
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10/08/2020
Assessing Phrasal Representation and Composition in Transformers
Deep transformer models have pushed performance on NLP tasks to new limi...
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10/06/2020
Exploring BERT's Sensitivity to Lexical Cues using Tests from Semantic Priming
Models trained to estimate word probabilities in context have become ubi...
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10/06/2020
Learning to Ignore: Long Document Coreference with Bounded Memory Neural Networks
Long document coreference resolution remains a challenging task due to t...
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08/16/2020
Adding Recurrence to Pretrained Transformers for Improved Efficiency and Context Size
Fine-tuning a pretrained transformer for a downstream task has become a ...
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05/06/2020
PeTra: A Sparsely Supervised Memory Model for People Tracking
We propose PeTra, a memory-augmented neural network designed to track en...
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05/04/2020
Spying on your neighbors: Fine-grained probing of contextual embeddings for information about surrounding words
Although models using contextual word embeddings have achieved state-of-...
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07/31/2019
What BERT is not: Lessons from a new suite of psycholinguistic diagnostics for language models
Pre-training by language modeling has become a popular and successful ap...
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09/11/2018
Assessing Composition in Sentence Vector Representations
An important component of achieving language understanding is mastering ...
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11/04/2017