Papers by Anna Mosolova
In the LLM era, Word Sense Induction remains unsolved (2025.findings-acl)
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| Challenge: | Existing word sense induction methods rely on predefined sense inventories of arbitrary granularity and require labor intensive sense-annotated data. |
| Approach: | They propose to evaluate an LLM-based word sense induction method for English . they use data augmentation sources, corpus and lexicon, and semi-supervised scenarios to augment the data. |
| Outcome: | The proposed method surpasses the previous SOTA system on a English set by 3.3%. |
Injecting Wiktionary to improve token-level contextual representations using contrastive learning (2024.eacl-short)
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| Challenge: | lexical semantics tasks require contextual word embeddings that are not blind to context, despite the fact that vectors of the same meaning are too different. |
| Approach: | They propose to fine-tune pre-trained language models by using automatically self-augmented examples to target contextual word embeddings. |
| Outcome: | The proposed method achieves significant improvements on the original WiC test set and in two new tests. |