no code implementations • 12 Mar 2024 • Andreas Damianou, Francesco Fabbri, Paul Gigioli, Marco De Nadai, Alice Wang, Enrico Palumbo, Mounia Lalmas
In the realm of personalization, integrating diverse information sources such as consumption signals and content-based representations is becoming increasingly critical to build state-of-the-art solutions.
no code implementations • 21 Mar 2023 • Gustavo Penha, Enrico Palumbo, Maryam Aziz, Alice Wang, Hugues Bouchard
A pre-requisite to discover an entity, e. g. a book, with a search engine is that the entity is retrievable, i. e. there are queries for which the system will surface such entity in the top results.
no code implementations • 15 Jun 2022 • Jack FitzGerald, Shankar Ananthakrishnan, Konstantine Arkoudas, Davide Bernardi, Abhishek Bhagia, Claudio Delli Bovi, Jin Cao, Rakesh Chada, Amit Chauhan, Luoxin Chen, Anurag Dwarakanath, Satyam Dwivedi, Turan Gojayev, Karthik Gopalakrishnan, Thomas Gueudre, Dilek Hakkani-Tur, Wael Hamza, Jonathan Hueser, Kevin Martin Jose, Haidar Khan, Beiye Liu, Jianhua Lu, Alessandro Manzotti, Pradeep Natarajan, Karolina Owczarzak, Gokmen Oz, Enrico Palumbo, Charith Peris, Chandana Satya Prakash, Stephen Rawls, Andy Rosenbaum, Anjali Shenoy, Saleh Soltan, Mukund Harakere Sridhar, Liz Tan, Fabian Triefenbach, Pan Wei, Haiyang Yu, Shuai Zheng, Gokhan Tur, Prem Natarajan
We present results from a large-scale experiment on pretraining encoders with non-embedding parameter counts ranging from 700M to 9. 3B, their subsequent distillation into smaller models ranging from 17M-170M parameters, and their application to the Natural Language Understanding (NLU) component of a virtual assistant system.
Cross-Lingual Natural Language Inference intent-classification +5
no code implementations • COLING 2020 • Enrico Palumbo, Andrea Mezzalira, Cristina Marco, Alessandro Manzotti, Daniele Amberti
In this paper, we introduce the task of generating a test set with high semantic diversity for NLU evaluation in dialog systems and we describe an approach to address it.
1 code implementation • 11 Oct 2018 • Diego Monti, Enrico Palumbo, Giuseppe Rizzo, Maurizio Morisio
In this paper, we present sequeval, a software tool capable of performing the offline evaluation of a recommender system designed to suggest a sequence of items.
Information Retrieval
no code implementations • SEMEVAL 2017 • Rapha{\"e}l Troncy, Enrico Palumbo, Efstratios Sygkounas, Giuseppe Rizzo
In this paper, we describe the participation of the SentiME++ system to the SemEval 2017 Task 4A {``}Sentiment Analysis in Twitter{''} that aims to classify whether English tweets are of positive, neutral or negative sentiment.