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Found 5 papers, 2 papers with code
Defending against Insertion-based Textual Backdoor Attacks via Attribution
Textual backdoor attack, as a novel attack model, has been shown to be effective in adding a backdoor to the model during training.
ChatGPT as an Attack Tool: Stealthy Textual Backdoor Attack via Blackbox Generative Model Trigger
Textual backdoor attacks pose a practical threat to existing systems, as they can compromise the model by inserting imperceptible triggers into inputs and manipulating labels in the training dataset.
IDPG: An Instance-Dependent Prompt Generation Method
Prompt tuning is a new, efficient NLP transfer learning paradigm that adds a task-specific prompt in each input instance during the model training stage.
PharmMT: A Neural Machine Translation Approach to Simplify Prescription Directions
We propose a novel machine translation-based approach, PharmMT, to automatically and reliably simplify prescription directions into patient-friendly language, thereby significantly reducing pharmacist workload.
LIREx: Augmenting Language Inference with Relevant Explanation
Natural language explanations (NLEs) are a special form of data annotation in which annotators identify rationales (most significant text tokens) when assigning labels to data instances, and write out explanations for the labels in natural language based on the rationales.
