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Enhance Robustness of Language Models Against Variation Attack through Graph Integration
The widespread use of pre-trained language models (PLMs) in natural language processing (NLP) has greatly improved performance outcomes.
Low-Resource Multi-Granularity Academic Function Recognition Based on Multiple Prompt Knowledge
Inspired by recent advancement in prompt learning, in this paper, we propose the Mix Prompt Tuning (MPT), which is a semi-supervised method to alleviate the dependence on annotated data and improve the performance of multi-granularity academic function recognition tasks with a small number of labeled examples.
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