논문들
1.Distributed Representations of Words and Phrases and their Compositionality
arxiv: https://arxiv.org/abs/1310.4546date: 05/11/2022Mikolov, T., Sutskever, I., Chen, K., Corrado, G. S., & Dean, J. (2013). Distributed repres
2.Attention Is All You Need
arxiv: https://arxiv.org/abs/1706.03762date: 05/23/2022Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., ... & Polosu
3.BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
arxiv: https://arxiv.org/abs/1810.04805date: 05/28/2022Devlin, J., Chang, M. W., Lee, K., & Toutanova, K. (2018). Bert: Pre-training of deep bidi
4.RoBERTa: A Robustly Optimized BERT Pretraining Approach
arxiv: https://arxiv.org/abs/1907.11692date: 05/29/2022Liu, Y., Ott, M., Goyal, N., Du, J., Joshi, M., Chen, D., ... & Stoyanov, V. (2019). Rober
5.ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
arxiv: https://arxiv.org/abs/1909.11942date: 06/06/2022Lan, Z., Chen, M., Goodman, S., Gimpel, K., Sharma, P., & Soricut, R. (2019). Albert: A li
6.BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension
arxiv: https://arxiv.org/abs/1910.13461date: 09/05/2022Lewis, M., Liu, Y., Goyal, N., Ghazvininejad, M., Mohamed, A., Levy, O., ... & Zettlemoyer
7.Language Models are Unsupervised Multitask Learners
date: 09/12/2022Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., & Sutskever, I. (2019). Language models are unsupervised multitask learners. Ope
8.Language Models are Few-Shot Learners
arxiv: https://arxiv.org/abs/2005.14165date: 09/19/2022Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., ... & Amodei, D.
9.ERNIE: Enhanced Language Representation with Informative Entities
arxiv: https://arxiv.org/abs/1905.07129date: 09/26/2022Zhang, Z., Han, X., Liu, Z., Jiang, X., Sun, M., & Liu, Q. (2019). ERNIE: Enhanced languag
10.Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing
arxiv: https://arxiv.org/abs/2107.13586date: 10/03/2022Liu, P., Yuan, W., Fu, J., Jiang, Z., Hayashi, H., & Neubig, G. (2021). Pre-train, prompt,
11.Video-guided machine translation via dual-level back-translation
Chen, S., Zeng, Y., Cao, D., & Lu, S. (2022). Video-guided machine translation via dual-level back-translation. Knowledge-Based Systems, 245, 108598.P
12.Vision talks: Visual relationship-enhanced transformer for video-guided machine translation
Chen, S., Zeng, Y., Cao, D., & Lu, S. (2022). Vision talks: Visual relationship-enhanced transformer for video-guided machine translation. Expert Syst
13.Incorporating Global Visual Features into Attention-Based Neural Machine Translation
Calixto, I., Liu, Q., & Campbell, N. (2017). Incorporating global visual features into attention-based neural machine translation. arXiv preprint arXi