We argue that, when establishing and benchmarking Machine Learning (ML)
...
We motivate why the science of learning to reject model predictions is
c...
A prominent approach to build datasets for training task-oriented bots i...
Crowdsourcing is being increasingly adopted as a platform to run studies...
Hybrid crowd-machine classifiers can achieve superior performance by
com...
Chatbots are emerging as a promising platform for accessing and deliveri...
This paper explores and offers guidance on a specific and relevant probl...
This paper reports on the challenges and lessons we learned while runnin...
Chatbots are software agents that are able to interact with humans in na...
Data integration has been studied extensively for decades and approached...
We present CrowdHub, a tool for running systematic evaluations of task
d...
Text classification is one of the most common goals of machine learning ...
This paper discusses how crowd and machine classifiers can be efficientl...
Social participation is known to bring great benefits to the health and
...
In this paper we explore the feasibility and design challenges in suppor...
Friendships and social interactions are renown contributors to wellbeing...
In this paper and demo we present a crowd and crowd+AI based system, cal...
In this work-in-progress paper we discuss the challenges in identifying
...
In this paper we describe how crowd and machine classifier can be effici...
Systematic literature reviews (SLRs) are one of the most common and usef...
In this paper we draw attention to the challenges of managing software
p...
At present, bots are still in their preliminary stages of development. M...
Literature reviews allow scientists to stand on the shoulders of giants,...