The proceedings of NL4AI 2019 are online on CEUR.
14:10-15:20 Keynote: Albert Gatt
15:20-15:45 Dagmar Monett and Christian Winkler
Using AI to Understand Intelligence: The Search for a Catalog of Intelligence Capabilities
16:15-16:40 Giuseppe Gambino and Roberto Pirrone
Investigating Embeddings for Sentiment Analysis in Italian
16:45-17:10 Marco Polignano, Pierpaolo Basile, Marco de Gemmis and Giovanni Semeraro
Hate Speech Detection through AlBERTo Italian Language Understanding Model
17:10-17:35 Anupama Arukgoda and A. R. Weerasinghe
Improving Sinhala-Tamil Translation through Deep Learning Techniques
17:35-18:00 Buddhi Kothalawala, Ruvan Weerasinghe and Prabhash Kumarasinghe
Online Learning for Solving Data Availability Problem in Natural Language Processing
15:00-15:25 Michael Richter and Tariq Yousef
Predicting default and non-default aspectual coding: Impact and density of information features
15:25-15:50 Andrea Amelio Ravelli, Lorenzo Gregori and Rossella Varvara
Comparing Ref-Vectors and word embeddings in a verb semantic similarity task
16:15-17:25 Keynote: Roberto Basili
17:25-17:50 Alexander Frummet, David Elsweiler and Bernd Ludwig
Detecting domain-specific information needs in conversational search dialogues
Albert Gatt is a Senior Lecturer and Director at Institute of Linguistics and Language Technology, University of Malta. He is a member of the RiVaL (Research in Vision and Language) research group and affiliated with the Blockchain research group. His research mostly focusses on the generation of language by machines (a.k.a. Natural Language Generation) and the production of language by humans.
Title: Grounding Natural Language Inference: Classifying and Generating Entailments using Visual Information
Roberto Basili is a Professor at the Department of Computer Science of the University of Roma, Tor Vergata and member of the Artificial Intelligence group at Tor Vergata (ART) since 1991. His research is on Natural Language Processing, Machine Learning, knowledge representation and applications such as Information Retrieval and Semantic Web.
Title: Inside NLP systems: between representation learning and ethics.
Abstract: Ethics is a crucial problem for current AI research for the widespread adoption of intelligent systems and devices. Although ethics has been studied in AI under several perspectives, the role of natural language
learning has not yet fully outlined. Rather than a linguistic perspective on ethics, that recently characterize a large set of studies on neural NLP, in the talk I will try to discuss role and perspectives in the use of linguistic information for the explanation of neural models, and how these latter are connected with ethically sustainable systems.