Papers by Kaihao Guo
ZeroAE: Pre-trained Language Model based Autoencoder for Transductive Zero-shot Text Classification (2023.findings-acl)
Copied to clipboard
| Challenge: | Existing methods for text classification use only encoders or decoders that do not allow for the use of labels in unseen domains. |
| Approach: | They propose an autoencoder that encodes text into two disentangled spaces and decodes it to generate text with labels in the unseen domains. |
| Outcome: | The proposed model outperforms the existing methods in label-partially-unseen and label-fully-un-seeen scenarios and even outperfects the SOTA methods. |
Learning Numeral Embedding (2020.findings-emnlp)
Copied to clipboard
| Challenge: | Existing word embedding methods do not learn numeral embedds well because numerals are limited in number and their appearances in training corpora are highly scarce. |
| Approach: | They propose two numeral embedding methods that can handle the out-of-vocabulary problem for numerals. |
| Outcome: | The proposed methods can handle the out-of-vocabulary problem for numerals. |