activity
20162021
most citedChatbots as conversational healthcare services

129 citations · 203 across the 11 of their papers we have counts for

collaborators

24 papers

cs.CL2021

Crowdsourcing Diverse Paraphrases for Training Task-oriented Bots

Jorge Ramírez, Auday Berro, Marcos Baez +2

A prominent approach to build datasets for training task-oriented bots is crowd-based paraphrasing. Current approaches, however, assume the crowd would naturally provide diverse pa…

cs.HC2021

On the state of reporting in crowdsourcing experiments and a checklist to aid current practices

Jorge Ramírez, Burcu Sayin, Marcos Baez +4

Crowdsourcing is being increasingly adopted as a platform to run studies with human subjects. Running a crowdsourcing experiment involves several choices and strategies to successf…

cs.LG20213 cited

Active Hybrid Classification

Evgeny Krivosheev, Fabio Casati, Alessandro Bozzon

Hybrid crowd-machine classifiers can achieve superior performance by combining the cost-effectiveness of automatic classification with the accuracy of human judgment. This paper sh…

cs.HC2020

On the impact of predicate complexity in crowdsourced classification tasks

Jorge Ramírez, Marcos Baez, Fabio Casati +4

This paper explores and offers guidance on a specific and relevant problem in task design for crowdsourcing: how to formulate a complex question used to classify a set of items. In…

cs.HC2020129 cited

Chatbots as conversational healthcare services

Mlađan Jovanović, Marcos Baez, Fabio Casati

Chatbots are emerging as a promising platform for accessing and delivering healthcare services. The evidence is in the growing number of publicly available chatbots aiming at takin…

cs.HC2020

Challenges and strategies for running controlled crowdsourcing experiments

Jorge Ramírez, Marcos Baez, Fabio Casati +2

This paper reports on the challenges and lessons we learned while running controlled experiments in crowdsourcing platforms. Crowdsourcing is becoming an attractive technique to en…