research
∙
08/07/2023
COPA: Efficient Vision-Language Pre-training Through Collaborative Object- and Patch-Text Alignment
Vision-Language Pre-training (VLP) methods based on object detection enj...
share
research
∙
07/17/2023
BUS:Efficient and Effective Vision-language Pre-training with Bottom-Up Patch Summarization
Vision Transformer (ViT) based Vision-Language Pre-training (VLP) models...
research
∙
02/01/2023
mPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and Video
Recent years have witnessed a big convergence of language, vision, and m...
research
∙
05/24/2022
mPLUG: Effective and Efficient Vision-Language Learning by Cross-modal Skip-connections
Large-scale pretrained foundation models have been an emerging paradigm ...
research
∙
11/17/2021
Achieving Human Parity on Visual Question Answering
The Visual Question Answering (VQA) task utilizes both visual image and ...
research
∙
08/21/2021
Grid-VLP: Revisiting Grid Features for Vision-Language Pre-training
Existing approaches to vision-language pre-training (VLP) heavily rely o...
research
∙
06/03/2021
E2E-VLP: End-to-End Vision-Language Pre-training Enhanced by Visual Learning
Vision-language pre-training (VLP) on large-scale image-text pairs has a...
research
∙
05/24/2021
StructuralLM: Structural Pre-training for Form Understanding
Large pre-trained language models achieve state-of-the-art results when ...
research
∙
03/14/2021
SemVLP: Vision-Language Pre-training by Aligning Semantics at Multiple Levels
Vision-language pre-training (VLP) on large-scale image-text pairs has r...
research
∙
11/29/2020
Latent Template Induction with Gumbel-CRFs
Learning to control the structure of sentences is a challenging problem ...
research
∙
10/30/2020
VECO: Variable Encoder-decoder Pre-training for Cross-lingual Understanding and Generation
Recent studies about learning multilingual representations have achieved...
research
∙
04/14/2020
PALM: Pre-training an Autoencoding Autoregressive Language Model for Context-conditioned Generation
Self-supervised pre-training has emerged as a powerful technique for nat...
research
∙
09/08/2019
Symmetric Regularization based BERT for Pair-wise Semantic Reasoning
The ability of semantic reasoning over the sentence pair is essential fo...
research
∙
09/06/2019
Incorporating External Knowledge into Machine Reading for Generative Question Answering
Commonsense and background knowledge is required for a QA model to answe...
research
∙
08/13/2019
StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding
Recently, the pre-trained language model, BERT (Devlin et al.(2018)Devli...
research
∙
11/28/2018
A Deep Cascade Model for Multi-Document Reading Comprehension
A fundamental trade-off between effectiveness and efficiency needs to be...
research
∙
09/29/2017
A Neural Comprehensive Ranker (NCR) for Open-Domain Question Answering
This paper proposes a novel neural machine reading model for open-domain...
research
∙
09/27/2017
