Papers with clean mapping
NUANCED: Natural Utterance Annotation for Nuanced Conversation with Estimated Distributions (2021.findings-emnlp)
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| Challenge: | Existing conversational systems are agent-centric, which assumes the user utterances will closely follow the system ontology. |
| Approach: | They build a dataset that maps user preferences to an ontology and model user preferences as estimated distributions over the system ontologies. |
| Outcome: | The proposed system can be used to push existing research from agent-centric to user-centric. |
Acquiring Clean Language Models from Backdoor Poisoned Datasets by Downscaling Frequency Space (2024.acl-long)
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| Challenge: | Prior work attempts to mitigate backdoor learning during training LMs on poisoned datasets . backdoor attack poisons a small portion of training data by implanting specific text patterns . |
| Approach: | They propose a multi-scale low-rank adaptive model that prioritizes learning of clean mapping . they propose radial scalings to reduce the success rate of diverse backdoor attacks . |
| Outcome: | The proposed model outperforms baselines significantly in the frequency space . it reduces the success rate of diverse backdoor attacks to below 15% across datasets . |