no code implementations • 29 May 2023 • Amin Beheshti, Jian Yang, Quan Z. Sheng, Boualem Benatallah, Fabio Casati, Schahram Dustdar, Hamid Reza Motahari Nezhad, Xuyun Zhang, Shan Xue
We introduce ProcessGPT as a new technology that has the potential to enhance decision-making in data-centric and knowledge-intensive processes.
no code implementations • 30 Sep 2022 • Burcu Sayin, Fabio Casati, Andrea Passerini, Jie Yang, Xinyue Chen
In this paper, we argue that the way we have been training and evaluating ML models has largely forgotten the fact that they are applied in an organization or societal context as they provide value to people.
no code implementations • 13 Dec 2021 • Fabio Casati, Pierre-André Noël, Jie Yang
We argue that, when establishing and benchmarking Machine Learning (ML) models, the research community should favour evaluation metrics that better capture the value delivered by their model in practical applications.
no code implementations • 11 Nov 2021 • Burcu Sayin, Jie Yang, Andrea Passerini, Fabio Casati
We motivate why the science of learning to reject model predictions is central to ML, and why human computation has a lead role in this effort.
no code implementations • 29 Sep 2021 • Yacine GACI, Boualem Benatallah, Fabio Casati, Khalid Benabdeslem
Recent studies in fair Representation Learning have observed a strong inclination for natural language processing (NLP) models to exhibit discriminatory stereotypes across gender, religion, race and many such social constructs.
no code implementations • 20 Sep 2021 • Jorge Ramírez, Auday Berro, Marcos Baez, Boualem Benatallah, Fabio Casati
A prominent approach to build datasets for training task-oriented bots is crowd-based paraphrasing.
no code implementations • 21 Jan 2021 • 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.
no code implementations • 8 Nov 2020 • Mlađan Jovanović, Marcos Baez, Fabio Casati
Chatbots are emerging as a promising platform for accessing and delivering healthcare services.
no code implementations • 17 Jan 2020 • Evgeny Krivosheev, Mattia Atzeni, Katsiaryna Mirylenka, Paolo Scotton, Fabio Casati
In this work, we propose a general approach to modeling and integrating entities from structured data, such as relational databases, as well as unstructured sources, such as free text from news articles.
no code implementations • 1 Apr 2019 • Evgeny Krivosheev, Fabio Casati, Marcos Baez, Boualem Benatallah
This paper discusses how crowd and machine classifiers can be efficiently combined to screen items that satisfy a set of predicates.
no code implementations • 31 May 2018 • Svetlana Nikitina, Florian Daniel, Marcos Baez, Fabio Casati
In this work-in-progress paper we discuss the challenges in identifying effective and scalable crowd-based strategies for designing content, conversation logic, and meaningful metrics for a reminiscence chatbot targeted at older adults.
no code implementations • 21 Mar 2018 • Evgeny Krivosheev, Bahareh Harandizadeh, Fabio Casati, Boualem Benatallah
In this paper we describe how crowd and machine classifier can be efficiently combined to screen items that satisfy a set of predicates.