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 …
An analysis of graph convolutional networks and recent datasets for visual question answering
AA Yusuf, F Chong, M Xianling - Artificial Intelligence Review, 2022 - Springer
Graph neural network is a deep learning approach widely applied on structural and non-
structural scenarios due to its substantial performance and interpretability recently. In a non …
structural scenarios due to its substantial performance and interpretability recently. In a non …
Unifying large language models and knowledge graphs: A roadmap
Large language models (LLMs), such as ChatGPT and GPT4, are making new waves in the
field of natural language processing and artificial intelligence, due to their emergent ability …
field of natural language processing and artificial intelligence, due to their emergent ability …
A-okvqa: A benchmark for visual question answering using world knowledge
Abstract The Visual Question Answering (VQA) task aspires to provide a meaningful testbed
for the development of AI models that can jointly reason over visual and natural language …
for the development of AI models that can jointly reason over visual and natural language …
Mathvista: Evaluating mathematical reasoning of foundation models in visual contexts
Although Large Language Models (LLMs) and Large Multimodal Models (LMMs) exhibit
impressive skills in various domains, their ability for mathematical reasoning within visual …
impressive skills in various domains, their ability for mathematical reasoning within visual …
Internlm-xcomposer2: Mastering free-form text-image composition and comprehension in vision-language large model
We introduce InternLM-XComposer2, a cutting-edge vision-language model excelling in free-
form text-image composition and comprehension. This model goes beyond conventional …
form text-image composition and comprehension. This model goes beyond conventional …
Multi-modal knowledge graph construction and application: A survey
Recent years have witnessed the resurgence of knowledge engineering which is featured
by the fast growth of knowledge graphs. However, most of existing knowledge graphs are …
by the fast growth of knowledge graphs. However, most of existing knowledge graphs are …
Revive: Regional visual representation matters in knowledge-based visual question answering
This paper revisits visual representation in knowledge-based visual question answering
(VQA) and demonstrates that using regional information in a better way can significantly …
(VQA) and demonstrates that using regional information in a better way can significantly …
How far are we to gpt-4v? closing the gap to commercial multimodal models with open-source suites
In this report, we introduce InternVL 1.5, an open-source multimodal large language model
(MLLM) to bridge the capability gap between open-source and proprietary commercial …
(MLLM) to bridge the capability gap between open-source and proprietary commercial …
Transform-retrieve-generate: Natural language-centric outside-knowledge visual question answering
Outside-knowledge visual question answering (OK-VQA) requires the agent to comprehend
the image, make use of relevant knowledge from the entire web, and digest all the …
the image, make use of relevant knowledge from the entire web, and digest all the …