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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 5 of 5 1 StructuralLM: Structural Pre-training for Form Understanding ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Bi, Bin; Huang, Fei. - : Underline Science Inc., 2021 BASE Show details 2 Addressing Semantic Drift in Generative Question Answering with Auxiliary Extraction ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Bi, Bin; Huang, Fei. - : Underline Science Inc., 2021 BASE Show details 3 E2E-VLP: End-to-End Vision-Language Pre-training Enhanced by Visual Learning ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Bi, Bin; Huang, Songfang; Huang, Fei; Li, Chenliang; Xiao, Wenming; Xu, Haiyang; Yan, Ming. - : Underline Science Inc., 2021 Abstract: Read paper: https://www.aclanthology.org/2021.acl-long.42 Abstract: Vision-language pre-training (VLP) on large-scale image-text pairs has achieved huge success for the cross-modal downstream tasks. The most existing pre-training methods mainly adopt a two-step training procedure, which firstly employs a pre-trained object detector to extract region-based visual features, then concatenates the image representation and text embedding as the input of Transformer to train. However, these methods face problems of using task-specific visual representation of the specific object detector for generic cross-modal understanding, and the computation inefficiency of two-stage pipeline. In this paper, we propose the first end-to-end vision-language pre-trained model for both V+L understanding and generation, namely E2E-VLP, where we build a unified Transformer framework to jointly learn visual representation, and semantic alignments between image and text. We incorporate the tasks of object detection and image ... Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics URL: https://underline.io/lecture/25397-e2e-vlp-end-to-end-vision-language-pre-training-enhanced-by-visual-learning https://dx.doi.org/10.48448/4a84-5s44 BASE Hide details 4 VECO: Variable and Flexible Cross-lingual Pre-training for Language Understanding and Generation ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Bi, Bin; Huang, Fei. - : Underline Science Inc., 2021 BASE Show details 5 VECO: Variable and Flexible Cross-lingual Pre-training for Language Understanding and Generation ... Luo, Fuli; Wang, Wei; Liu, Jiahao. - : arXiv, 2020 BASE Show details

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