Alexander Pugantsov

Alexander Pugantsov

Postdoctoral Researcher

Publications

You can also find my articles on my Google Scholar profile.

Conference Papers

Divergence-Based Domain Transferability for Zero-Shot Classification

Published in European Chapter of the Association for Computational Linguistics, 2023

Fine-tuning on intermediate tasks can enhance pretrained language models, but identifying related tasks is challenging and resource-intensive. This paper uses statistical measures of domain divergence to predict which task pairs are likely to yield performance benefits. Our method reduces the number of task combinations to test, cutting runtime by up to 40% while maintaining effectiveness.

Recommended citation: Pugantsov, A., & McCreadie, R. (2023). Divergence-Based Domain Transferability for Zero-Shot Classification. In Findings of the Association for Computational Linguistics: EACL 2023 (pp. 1649-1654).
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Identifying Suitable Tasks for Inductive Transfer Through the Analysis of Feature Attributions

Published in European Conference on Information Retrieval, 2022

Transfer learning often improves downstream task performance, but finding effective task pairings is computationally expensive due to trial-and-error. This paper predicts transferability between tasks using explainability techniques, comparing neural network activations of single-task models. Our approach reduces training time by up to 83.5% with minimal impact on performance.

Recommended citation: Pugantsov, A., & McCreadie, R. (2022). Identifying Suitable Tasks for Inductive Transfer Through the Analysis of Feature Attributions. In European Conference on Information Retrieval (pp. 137-143).
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