Over the last few years the sharing economy has been changing the way that people share
and conduct transactions in digital spaces. This research phenomenon has drawn scholars …

Crowdsourcing enables one to leverage on the intelligence and wisdom of potentially large
groups of individuals toward solving problems. Common problems approached with …

Human variation in labeling is often considered noise. Annotation projects for machine
learning (ML) aim at minimizing human label variation, with the assumption to maximize …

Large datasets have become commonplace in NLP research. However, the increased
emphasis on data quantity has made it challenging to assess the quality of data. We …

The de-facto approach to many vision tasks is to start from pretrained visual representations,
typically learned via supervised training on ImageNet. Recent methods have explored …

Most natural videos contain numerous events. For example, in a video of a" man playing a
piano", the video might also contain" another man dancing" or" a crowd clapping". We …

Despite progress in perceptual tasks such as image classification, computers still perform
poorly on cognitive tasks such as image description and question answering. Cognition is …

The classification performance of deep neural networks has begun to asymptote at near-
perfect levels. However, their ability to generalize outside the training set and their …

In this article, we introduce the task of visual grounding for remote sensing data (RSVG).
RSVG aims to localize the referred objects in remote sensing (RS) images with the guidance …

Modern neural networks have the capacity to overfit noisy labels frequently found in real-
world datasets. Although great progress has been made, existing techniques are very …