Papers by Daniil Cherniavskii
Acceptability Judgements via Examining the Topology of Attention Maps (2022.findings-emnlp)
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Daniil Cherniavskii, Eduard Tulchinskii, Vladislav Mikhailov, Irina Proskurina, Laida Kushnareva, Ekaterina Artemova, Serguei Barannikov, Irina Piontkovskaya, Dmitri Piontkovski, Evgeny Burnaev
| Challenge: | Acceptability judgments are a key component of generative linguistics, but their ability to judge grammatical acceptability has not been explored. |
| Approach: | They propose to exploit the geometric properties of the attention graph to evaluate the grammatical acceptability of sentences using topological data analysis. |
| Outcome: | The proposed approach outperforms nine statistical and Transformer LM baselines on the BLiMP benchmark and the human-level performance on the same benchmark. |
Artificial Text Detection via Examining the Topology of Attention Maps (2021.emnlp-main)
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Laida Kushnareva, Daniil Cherniavskii, Vladislav Mikhailov, Ekaterina Artemova, Serguei Barannikov, Alexander Bernstein, Irina Piontkovskaya, Dmitri Piontkovski, Evgeny Burnaev
| Challenge: | Existing methods for text detection lack interpretability and robustness towards unseen models. |
| Approach: | They propose three new types of interpretable topological features based on topological data analysis which is currently understudied in the field of NLP. |
| Outcome: | The proposed features outperform count- and neural-based baselines up to 10% on three common datasets and tend to be the most robust towards unseen GPT-style generation models. |