Papers with sentiment classification model
Zero-shot Approach to Overcome Perturbation Sensitivity of Prompts (2023.acl-long)
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| Challenge: | Recent studies have demonstrated that natural-language prompts can help to leverage the knowledge learned by pre-trained language models for the binary sentence-level sentiment classification task. |
| Approach: | They propose to use few-shot learning settings to fine-tune the sentiment classification model using manual or automatically generated prompts. |
| Outcome: | The proposed method outperforms the base prompt and the prompts generated using few-shot learning for the binary sentence-level sentiment classification task. |
Contrasting Human- and Machine-Generated Word-Level Adversarial Examples for Text Classification (2021.emnlp-main)
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| Challenge: | Recent work has raised the question of whether valid adversarial inputs are feasible. |
| Approach: | They analyze how human-generated adversarial examples compare to the best algorithms . they use crowdsourcing to modify words in an input text with immediate feedback . |
| Outcome: | The proposed algorithms are not more efficient than the best to generate natural-reading, sentiment-preserving examples. |