Papers by Viktoria Schram
Performance Prediction via Bayesian Matrix Factorisation for Multilingual Natural Language Processing Tasks (2023.eacl-main)
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| Challenge: | Performance prediction for natural language processing (NLP) is based on a framework of Bayesian matrix factorisation . it avoids hyperparameter tuning and provides uncertainty estimates over predictions. |
| Approach: | They propose to use Bayesian matrix factorisation to predict the performance of language pairs depicted by grey cells. |
| Outcome: | The proposed framework outperforms the state-of-the-art in several NLP benchmarks, including machine translation and cross-lingual entity linking. |