The multi-modal fusion in visual question answering: a review of attention mechanisms
Abstract Visual Question Answering (VQA) is a significant cross-disciplinary issue in the
fields of computer vision and natural language processing that requires a computer to output …
fields of computer vision and natural language processing that requires a computer to output …
Vision-language pre-training: Basics, recent advances, and future trends
This monograph surveys vision-language pre-training (VLP) methods for multimodal
intelligence that have been developed in the last few years. We group these approaches …
intelligence that have been developed in the last few years. We group these approaches …
Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation
Abstract Vision-Language Pre-training (VLP) has advanced the performance for many vision-
language tasks. However, most existing pre-trained models only excel in either …
language tasks. However, most existing pre-trained models only excel in either …
Prompt programming for large language models: Beyond the few-shot paradigm
L Reynolds, K McDonell - Extended abstracts of the 2021 CHI …, 2021 - dl.acm.org
Prevailing methods for mapping large generative language models to supervised tasks may
fail to sufficiently probe models' novel capabilities. Using GPT-3 as a case study, we show …
fail to sufficiently probe models' novel capabilities. Using GPT-3 as a case study, we show …
Recent advances in deep learning based dialogue systems: A systematic survey
Dialogue systems are a popular natural language processing (NLP) task as it is promising in
real-life applications. It is also a complicated task since many NLP tasks deserving study are …
real-life applications. It is also a complicated task since many NLP tasks deserving study are …
Large-scale adversarial training for vision-and-language representation learning
We present VILLA, the first known effort on large-scale adversarial training for vision-and-
language (V+ L) representation learning. VILLA consists of two training stages:(i) task …
language (V+ L) representation learning. VILLA consists of two training stages:(i) task …
Attention, please! A survey of neural attention models in deep learning
A de Santana Correia, EL Colombini - Artificial Intelligence Review, 2022 - Springer
In humans, Attention is a core property of all perceptual and cognitive operations. Given our
limited ability to process competing sources, attention mechanisms select, modulate, and …
limited ability to process competing sources, attention mechanisms select, modulate, and …
Two causal principles for improving visual dialog
This paper unravels the design tricks adopted by us, the champion team MReaL-BDAI, for
Visual Dialog Challenge 2019: two causal principles for improving Visual Dialog (VisDial) …
Visual Dialog Challenge 2019: two causal principles for improving Visual Dialog (VisDial) …
Utc: A unified transformer with inter-task contrastive learning for visual dialog
Visual Dialog aims to answer multi-round, interactive questions based on the dialog history
and image content. Existing methods either consider answer ranking and generating …
and image content. Existing methods either consider answer ranking and generating …
Large-scale pretraining for visual dialog: A simple state-of-the-art baseline
Prior work in visual dialog has focused on training deep neural models on VisDial in
isolation. Instead, we present an approach to leverage pretraining on related vision …
isolation. Instead, we present an approach to leverage pretraining on related vision …