Papers with OLM
Considering Likelihood in NLP Classification Explanations with Occlusion and Language Modeling (2020.acl-srw)
Copied to clipboard
| Challenge: | Existing explanation methods produce invalid or syntactically incorrect data, neglecting the improved abilities of recent NLP models. |
| Approach: | They propose an explanation method that combines occlusion and language models to sample valid and syntactically correct replacements with high likelihood, given the context of the original input. |
| Outcome: | The proposed method can sample valid and syntactically correct replacements with high likelihood, given the context of the original input. |
Adv-OLM: Generating Textual Adversaries via OLM (2021.eacl-main)
Copied to clipboard
| Challenge: | Recent studies have pointed out the vulnerability of deep learning models to adversarial attacks. |
| Approach: | They propose a black-box attack method that adapts the idea of Occlusion and Language Models to the current state of the art attack methods. |
| Outcome: | The proposed method outperforms existing methods on several text classification tasks. |