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TARGET: Template-Transferable Backdoor Attack Against Prompt-based NLP Models via GPT4
Most of the existing attack methods focus on inserting manually predefined templates as triggers in the pre-training phase to train the victim model and utilize the same triggers in the downstream task to perform inference, which tends to ignore the transferability and stealthiness of the templates.
COVER: A Heuristic Greedy Adversarial Attack on Prompt-based Learning in Language Models
Prompt-based learning has been proved to be an effective way in pre-trained language models (PLMs), especially in low-resource scenarios like few-shot settings.
Improving Chinese Segmentation-free Word Embedding With Unsupervised Association Measure
Recent work on segmentation-free word embedding(sembei) developed a new pipeline of word embedding for unsegmentated language while avoiding segmentation as a preprocessing step.
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