Jun 17, 2024 · This paper proposed a context-aware generative prompt tuning method which ensures the comprehensiveness of triplet extraction by modeling the ...

Aug 15, 2024 · In this paper, we propose a Generative context-Aware Prompt-tuning method (GAP) to address these limitations. Our method consists of three crucial modules.

Jun 8, 2024 · To this end, we propose a novel Context-Aware Generative Prompt Tuning (CAGPT) method which ensures the comprehensiveness of triplet extraction ...

A pretrained prompt generator module that extracts or generates the relation triggers from the context and embeds them into the prompt tokens;; An in-domain ...

GAP: A novel Generative context-Aware Prompt-tuning method for relation extraction · Zhenbin Chen, Zhixin Li, +2 authors. Huifang Ma · Published in Expert systems ...

Context-aware generative prompt tuning for relation extraction. International journal of machine learning and cybernetics, 2024-12, Vol.15 (12), p.5495-5508 ...

Prompt -tuning was proposed to bridge the gap between pretraining and downstream tasks, and it has achieved promising results in Relation Extraction (RE).

Inspired by the text infilling task for pre-training generative models that can flexibly predict missing spans, we pro- pose a novel generative prompt tuning ...

Chen et al. [3] proposes a Generative Context-Aware Prompt-tuning method which also tackles the problem of prompt template engineering. This work proposed a ...

Relation extraction is designed to extract semantic relation between predefined entities from text. Recently, prompt tuning has achieved promising results ...