May 6, 2024 · We propose a simple and effective strategy for few-shot and zero-shot text classification. We aim to liberate the model from the confines of seen classes.

Liberating Seen Classes: Boosting Few-Shot and Zero-Shot Text Classification via Anchor Generation and Classification Reframing. Han Liu1, Siyang Zhao1 ...

This work aims to liberate the model from the confines of seen classes, thereby enabling it to predict unseen categories without the necessity of training ...

Jul 31, 2024 · Few-shot and zero-shot text classification aim to recognize samples from novel classes with limited labeled samples or no labeled samples at ...

Feb 22, 2024 · On-demand video platform giving you access to lectures from conferences worldwide.

May 6, 2024 · This paper proposes a novel approach to few-shot and zero-shot text classification, which aims to recognize samples from novel classes with ...

Jul 31, 2024 · When using embedding models for zero-shot classification, rephrasing the class label to "This is seriously about 'LABEL'" gives higher accuracy vs. using LABEL ...

Liberating Seen Classes: Boosting Few-Shot and Zero-Shot Text Classification via Anchor Generation and Classification Reframing. Proceedings of the AAAI ...

Few-shot and zero-shot text classification aim to recognize samples from novel classes with limited labeled samples or no labeled samples at all. Binary ...

Liberating Seen Classes: Boosting Few-Shot and Zero-Shot Text Classification via Anchor Generation and Classification Reframing ... Few-Shot Font Generation ...