activity
20162023
most citedFILIP: Fine-grained Interactive Language-Image Pre-Training

206 citations · 488 across the 59 of their papers we have counts for

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Showing 2022Show all

26 papers · 1 filter

cs.CL2022★ 2 cited

Wukong-Reader: Multi-modal Pre-training for Fine-grained Visual Document Understanding

Haoli Bai, Zhiguang Liu, Xiaojun Meng +9

Unsupervised pre-training on millions of digital-born or scanned documents has shown promising advances in visual document understanding~(VDU). While various vision-language pre-tr…

cs.CL2022★ 1 cited

KPT: Keyword-guided Pre-training for Grounded Dialog Generation

Qi Zhu, Fei Mi, Zheng Zhang +6

Incorporating external knowledge into the response generation process is essential to building more helpful and reliable dialog agents. However, collecting knowledge-grounded conve…

cs.CL2022

Retrieval-based Disentangled Representation Learning with Natural Language Supervision

Jiawei Zhou, Xiaoguang Li, Lifeng Shang +3

Disentangled representation learning remains challenging as the underlying factors of variation in the data do not naturally exist. The inherent complexity of real-world data makes…

cs.CL2022

G-MAP: General Memory-Augmented Pre-trained Language Model for Domain Tasks

Zhongwei Wan, Yichun Yin, Wei Zhang +5

Recently, domain-specific PLMs have been proposed to boost the task performance of specific domains (e.g., biomedical and computer science) by continuing to pre-train general PLMs…

cs.CL2022★ 1 cited

Lexicon-injected Semantic Parsing for Task-Oriented Dialog

Xiaojun Meng, Wenlin Dai, Yasheng Wang +4

Recently, semantic parsing using hierarchical representations for dialog systems has captured substantial attention. Task-Oriented Parse (TOP), a tree representation with intents a…

cs.CV2022★ 1 cited

LiteVL: Efficient Video-Language Learning with Enhanced Spatial-Temporal Modeling

Dongsheng Chen, Chaofan Tao, Lu Hou +3

Recent large-scale video-language pre-trained models have shown appealing performance on various downstream tasks. However, the pre-training process is computationally expensive du…