2 code implementations • 19 Feb 2024 • Wei Jie Yeo, Ranjan Satapathy, Rick Siow Mong Goh, Erik Cambria
We present a comprehensive and multifaceted evaluation of interpretability, examining not only faithfulness but also robustness and utility across multiple commonsense reasoning benchmarks.
1 code implementation • 13 Feb 2024 • Wei Jie Yeo, Ranjan Satapathy, Erik Cambria
The increasing use of complex and opaque black box models requires the adoption of interpretable measures, one such option is extractive rationalizing models, which serve as a more interpretable alternative.
no code implementations • 21 Sep 2023 • Wei Jie Yeo, Wihan van der Heever, Rui Mao, Erik Cambria, Ranjan Satapathy, Gianmarco Mengaldo
The success of artificial intelligence (AI), and deep learning models in particular, has led to their widespread adoption across various industries due to their ability to process huge amounts of data and learn complex patterns.
no code implementations • 22 Jun 2023 • Yang Li, Kangbo Liu, Ranjan Satapathy, Suhang Wang, Erik Cambria
The objective of this study is to provide an overview of the current state-of-the-art in the field and highlight the latest trends in the development of recommender systems.
no code implementations • 5 Mar 2023 • Keane Ong, Wihan van der Heever, Ranjan Satapathy, Erik Cambria, Gianmarco Mengaldo
This paper presents a novel approach for explainability in financial analysis by deriving financially-explainable statistical relationships through aspect-based sentiment analysis, Pearson correlation, Granger causality & uncertainty coefficient.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +1
no code implementations • 14 Jan 2022 • Ranjan Satapathy, Shweta Pardeshi, Erik Cambria
The proposed approach reports baseline performances for both polarity detection and subjectivity detection.
no code implementations • 22 May 2019 • Nidhi Mishra, Manoj Ramanathan, Ranjan Satapathy, Erik Cambria, Nadia Magnenat-Thalmann
In this study, we propose to have a humanoid social robot, Nadine, as a customer service agent in an open social work environment.
no code implementations • 24 Apr 2019 • Ranjan Satapathy, Aalind Singh, Erik Cambria
The usage of microtext poses a considerable performance issue in concept-level sentiment analysis, since models are trained on standard words.