Foundations and Trends in Multimodal Machine Learning: Principles, Challenges, and Open Questions
Multimodal machine learning is a vibrant multi-disciplinary research field that aims to design
computer agents with intelligent capabilities such as understanding, reasoning, and learning …
computer agents with intelligent capabilities such as understanding, reasoning, and learning …
Foundations & trends in multimodal machine learning: Principles, challenges, and open questions
Multimodal machine learning is a vibrant multi-disciplinary research field that aims to design
computer agents with intelligent capabilities such as understanding, reasoning, and learning …
computer agents with intelligent capabilities such as understanding, reasoning, and learning …
Easily accessible text-to-image generation amplifies demographic stereotypes at large scale
Machine learning models that convert user-written text descriptions into images are now
widely available online and used by millions of users to generate millions of images a day …
widely available online and used by millions of users to generate millions of images a day …
[HTML][HTML] Cpt: Colorful prompt tuning for pre-trained vision-language models
Abstract Vision-Language Pre-training (VLP) models have shown promising capabilities in
grounding natural language in image data, facilitating a broad range of cross-modal tasks …
grounding natural language in image data, facilitating a broad range of cross-modal tasks …
Language (technology) is power: A critical survey of" bias" in nlp
We survey 146 papers analyzing" bias" in NLP systems, finding that their motivations are
often vague, inconsistent, and lacking in normative reasoning, despite the fact that …
often vague, inconsistent, and lacking in normative reasoning, despite the fact that …
Assessing cross-cultural alignment between ChatGPT and human societies: An empirical study
The recent release of ChatGPT has garnered widespread recognition for its exceptional
ability to generate human-like responses in dialogue. Given its usage by users from various …
ability to generate human-like responses in dialogue. Given its usage by users from various …
Cm3: A causal masked multimodal model of the internet
We introduce CM3, a family of causally masked generative models trained over a large
corpus of structured multi-modal documents that can contain both text and image tokens …
corpus of structured multi-modal documents that can contain both text and image tokens …
Dall-eval: Probing the reasoning skills and social biases of text-to-image generation models
Recently, DALL-E, a multimodal transformer language model, and its variants including
diffusion models have shown high-quality text-to-image generation capabilities. However …
diffusion models have shown high-quality text-to-image generation capabilities. However …
Debiased contrastive learning of unsupervised sentence representations
Recently, contrastive learning has been shown to be effective in improving pre-trained
language models (PLM) to derive high-quality sentence representations. It aims to pull close …
language models (PLM) to derive high-quality sentence representations. It aims to pull close …
[HTML][HTML] Multibench: Multiscale benchmarks for multimodal representation learning
Learning multimodal representations involves integrating information from multiple
heterogeneous sources of data. It is a challenging yet crucial area with numerous real-world …
heterogeneous sources of data. It is a challenging yet crucial area with numerous real-world …