Grafting Pre-trained Models for Multimodal Headline Generation
Comments Accepted by EMNLP 2022
期刊&会议
Conference on Empirical Methods in Natural Language Processing · 会议 · Natural Language Processing
Comments Accepted by EMNLP 2022
Comments Accepted by EMNLP 2022 Main Conference
Comments accepted at EMNLP 2022
Comments Accepted by EMNLP 2022 (18 pages)
Comments Findings of EMNLP 2022
Comments Accepted by EMNLP 2022 findings
Comments Findings of EMNLP 2022
Comments To appear in TACL 2022 and EMNLP 2022. The arXiv version is a pre-MIT Press publication version
Comments Accepted to EMNLP 2022
Comments Presented at EMNLP 2022 main conference
Comments arXiv admin note: substantial text overlap with arXiv:1908.06809
Journal ref EMNLP-IJCNLP 2019. 2019 Nov 4:128
Journal ref In Proceedings of EMNLP-IJCNLP 2019 Nov (pp. 3936-3945)
Comments To appear in EMNLP Findings 2022. The code is available at https://github.com/xingyizhao/TAMPERS
Comments Accepted at EMNLP 2022. Tiago Pimentel and Josef Valvoda contributed equally to this work. Code available in https://github.com/rycolab/attentional-probe
Comments Accepted in the Findings of EMNLP 2022
Comments EMNLP 2022
Comments accepted by EMNLP 2022
Comments Accepted by EMNLP 2022
Comments Accepted for publication at SereTOD Workshop - EMNLP 2022
Comments Accepted at the FinNLP workshop part of the EMNLP 2022 conference
Comments Accepted to EMNLP 2022
Comments EMNLP 2022
Comments 17 pages, EMNLP 2022 Main Conference
Comments EMNLP 2022
Comments EMNLP'22 Industry Track. Extended Abstract presented at Machine Learning for Health (ML4H) symposium 2022, November 28th, 2022, New Orleans, United States & Virtual, http://www.ml4h.cc, 16 pages
Comments Accepted to EMNLP 2022 main conference
Comments Findings of EMNLP 2022
Comments Accepted to EMNLP 2022
Comments Accepted to GEM Workshop, EMNLP 2022
Comments Accepted to EMNLP 2022; 34 pages