no code implementations • NAACL (ACL) 2022 • Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Navid Nobani, Andrea Seveso
The recent growth of black-box machine-learning methods in data analysis has increased the demand for explanation methods and tools to understand their behaviour and assist human-ML model cooperation.
1 code implementation • 1 Feb 2024 • Weijie Xu, Zicheng Huang, Wenxiang Hu, Xi Fang, Rajesh Kumar Cherukuri, Naumaan Nayyar, Lorenzo Malandri, Srinivasan H. Sengamedu
The data generation pipeline is transferable and can be easily adapted for labeled conversation data generation in other domains.
1 code implementation • Decision Support Systems 2023 • Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Andrea Seveso
Explaining how two machine learning classification models differ in their behaviour is gaining significance in eXplainable AI, given the increasing diffusion of learning-based decision support systems.
Counterfactual Explanation Explainable artificial intelligence
1 code implementation • Cognitive Computation 2022 • Anna Giabelli, Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Navid Nobani
Then, we train several embedding models on a text corpus and select the best model, that is, the model that maximizes the correlation between the HSS and the cosine similarity of the pair of words that are in both the taxonomy and the corpus.
1 code implementation • Information Fusion 2021 • Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica, Andrea Seveso, Navid Nobani
The need for explanations of ML systems is growing as new models outperform their predecessors while becoming more complex and less comprehensible for their end-users.
no code implementations • COLING 2020 • Frank Xing, Lorenzo Malandri, Yue Zhang, Erik Cambria
The recent dominance of machine learning-based natural language processing methods has fostered the culture of overemphasizing model accuracies rather than studying the reasons behind their errors.
Autonomous Driving Cultural Vocal Bursts Intensity Prediction +1
1 code implementation • 27 Feb 2018 • Frank Z. Xing, Erik Cambria, Lorenzo Malandri, Carlo Vercellis
Along with the advance of opinion mining techniques, public mood has been found to be a key element for stock market prediction.