Papers by Verena Weber
Regression-Free Model Updates for Spoken Language Understanding (2023.acl-industry)
Copied to clipboard
| Challenge: | Recent work has proposed methods for minimizing regressions caused by model updates . focus is on spoken language understanding models, which are unexplored . |
| Approach: | They propose a focal distillation technique to reduce regressions in goal-oriented dialog systems . they also evaluate its effectiveness for key language understanding tasks . |
| Outcome: | The proposed technique outperforms naive supervised training in mislabeled data and label expansion settings. |
Semi-supervised Adversarial Text Generation based on Seq2Seq models (2022.emnlp-industry)
Copied to clipboard
| Challenge: | In contrast, adversarial training has been used in computer vision to improve models’ robustness due to the discrete nature of text. |
| Approach: | They propose a way to generate adversarial samples by using pseudo-labeled in-domain text data to train a seq2seq model for adversarials and combine it with paraphrase detection. |
| Outcome: | The proposed model generates realistic and relevant adversarial samples compared to other state-of-the-art models and recovers up to 70% of errors. |