GAP: A novel Generative context-Aware Prompt-tuning method for relation extraction

Author:

Chen Zhenbin,Li ZhixinORCID,Zeng Yufei,Zhang Canlong,Ma Huifang

Funder

National Natural Science Foundation of China

Guangxi Natural Science Foundation

Publisher

Elsevier BV

Reference88 articles.

1. Alt, C., Gabryszak, A., & Hennig, L. (2020). TACRED Revisited: A Thorough Evaluation of the TACRED Relation Extraction Task. In Proceedings of the 58th annual meeting of the association for computational linguistics (pp. 1558–1569).

2. Bahdanau, D., Cho, K., & Bengio, Y. (2015). Neural machine translation by jointly learning to align and translate. In 3rd international conference on learning representations.

3. Can the transformer be used as a drop-in replacement for RNNs in text-generating GANs?;Blin,2021

4. Comparison of LSTM, GRU and transformer neural network architecture for prediction of wind turbine variables;Buestán-Andrade,2023

5. A shortest path dependency kernel for relation extraction;Bunescu,2005

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1. Retrieving memory as prompts for continual relation extraction;Expert Systems with Applications;2024-12

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