Papers by Victor Pellegrain
Transductive Learning for Textual Few-Shot Classification in API-based Embedding Models (2023.emnlp-main)
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Pierre Colombo, Victor Pellegrain, Malik Boudiaf, Myriam Tami, Victor Storchan, Ismail Ayed, Pablo Piantanida
| Challenge: | Proprietary and closed APIs are impacting the practical applications of natural language processing. |
| Approach: | They propose a scenario where a pre-trained model is served through a gated API . they propose 'transductive inference' that leverages statistics of unlabelled data . |
| Outcome: | The proposed model performs a few-shot classification task with unlabelled data using a gated API . the proposed model can be used to perform the task with a handful of classes . |