1 code implementation • 14 Mar 2024 • Zhifan Sun, Antonio Valerio Miceli-Barone
Large Language Models (LLMs) are increasingly becoming the preferred foundation platforms for many Natural Language Processing tasks such as Machine Translation, owing to their quality often comparable to or better than task-specific models, and the simplicity of specifying the task through natural language instructions or in-context examples.
1 code implementation • 26 Oct 2023 • Antonio Valerio Miceli-Barone, Alex Lascarides, Craig Innes
Simulation is an invaluable tool for developing and evaluating controllers for self-driving cars.
1 code implementation • 31 May 2023 • Paul Darm, Antonio Valerio Miceli-Barone, Shay B. Cohen, Annalisa Riccardi
In this work we present a system, developed for the European Space Agency (ESA), that can answer complex natural language queries, to support engineers in accessing the information contained in a KB that models the orbital space debris environment.
1 code implementation • 24 May 2023 • Antonio Valerio Miceli-Barone, Fazl Barez, Ioannis Konstas, Shay B. Cohen
Large Language Models (LLMs) have successfully been applied to code generation tasks, raising the question of how well these models understand programming.
no code implementations • RepL4NLP (ACL) 2022 • Antonio Valerio Miceli-Barone, Alexandra Birch, Rico Sennrich
Neural machine learning models can successfully model language that is similar to their training distribution, but they are highly susceptible to degradation under distribution shift, which occurs in many practical applications when processing out-of-domain (OOD) text.