Papers by Lisa Bylinina
Transformers in the loop: Polarity in neural models of language (2022.acl-long)
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| Challenge: | Recent Transformer-based language representation models (LRMs) show impressive results on practical text analysis tasks, but do they have access to complex linguistic notions? |
| Approach: | They propose to use polarity as a case study to compare metrics derived from language models to human judgments obtained in psycholinguistic experiments. |
| Outcome: | The proposed model is more accurate than linguistic theory predictions for polarity, and allows us to use language models to discover new insights into natural language grammar beyond existing linguistic theories. |
Leverage Points in Modality Shifts: Comparing Language-only and Multimodal Word Representations (2023.starsem-1)
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| Challenge: | a recent study of the effect of visual grounding on language representations has given a new life to the debate around extractability and quality of semantic information in representations trained solely on textual input. |
| Approach: | They compare word embeddings from vision-and-language models to text-only models . they identify meaning properties and relations that characterize words whose embeddements are most affected by visual grounding . |
| Outcome: | The proposed model differs from text-only models on semantic representations of language . the study is the first large-scale study of the effect of visual grounding on language representations . |
Connecting degree and polarity: An artificial language learning study (2023.emnlp-main)
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| Challenge: | Existing studies have shown that degree modifiers are related to sentence polarity, but they are not related to the grammatical number of an expression. |
| Approach: | They propose to generalize degree modifiers to their polarity sensitivity in pre-trained language models by applying the Artificial Language Learning experimental paradigm from psycholinguistics to a neural language model. |
| Outcome: | The proposed generalisations are consistent with existing linguistic observations that relate de-gree semantics to polarity sensitivity, including the main one: low degree semantics is associated with preference towards positive polarities. |