Together We Can: Multilingual Automatic Post-Editing for Low-Resource Languages
Comments Accepted at Findings of EMNLP 2024
期刊&会议
Conference on Empirical Methods in Natural Language Processing · 会议 · Natural Language Processing
Comments Accepted at Findings of EMNLP 2024
Comments Accepted at EMNLP-2024
Comments EMNLP 2024 main conference proceedings
Comments Accepted by EMNLP 2024
Comments Accepted to EMNLP 2024
Comments This paper is accepted at EMNLP 2024 Main
Comments Accepted as main paper in EMNLP 2024
Comments 40 pages. Findings of EMNLP 2024
Comments Accepted at EMNLP 2024. Code and data: https://github.com/UKPLab/arxiv2024-attribute-or-abstain
Comments 12 pages, 6 figures. Accepted as main paper in EMNLP 2024
Comments EMNLP 2024
Comments Accepted to EMNLP 2024 Main Conference
Comments EMNLP 2024 Findings
Comments EMNLP 2024; 9 pages, 3 figures
Comments 13 pages, 8 figures, The 2024 Conference on Empirical Methods in Natural Language Processing
Comments Accepted in GenBench EMNLP 2024
Comments Accepted in EMNLP 2024
Journal ref EMNLP 2024
Comments Accepted by EMNLP 2024 Findings
Comments EMNLP 2024 (Main)
Journal ref EMNLP 2024 Demo Track
Comments EMNLP 2024, Main, Poster
Comments Accepted by EMNLP Main 2024
Comments Oral, EMNLP 2024 Industry Track. 31 pages, 11 figures, Project: https://fly1113.github.io/MFI/
Comments CONLL 2024 (EMNLP 2024)
Comments EMNLP 2024, camera ready
Comments Accepted to EMNLP 2024 Main Conference
Comments Wenda Xu and Jiachen Li contributed equally. Accepted by EMNLP 2024
Comments Findings of EMNLP Camera-ready version
Comments Accepted to EMNLP 2024 Findings. The main paper is 9 pages long, with 16 pages total. The code, results, dataset, and additional resources are available on the project website: https://llm-authorship.github.io/