2 code implementations • 1 Jun 2023 • Silvia Terragni, Modestas Filipavicius, Nghia Khau, Bruna Guedes, André Manso, Roland Mathis
This paper presents a novel application of large language models in user simulation for task-oriented dialog systems, specifically focusing on an in-context learning approach.
no code implementations • 29 Mar 2018 • Matteo Manica, Joris Cadow, Roland Mathis, María Rodríguez Martínez
Reliable identification of molecular biomarkers is essential for accurate patient stratification.
no code implementations • 18 Aug 2018 • Ali Oskooei, Matteo Manica, Roland Mathis, Maria Rodriguez Martinez
We present the Network-based Biased Tree Ensembles (NetBiTE) method for drug sensitivity prediction and drug sensitivity biomarker identification in cancer using a combination of prior knowledge and gene expression data.
no code implementations • 16 Jan 2017 • Manuel Le Gallo, Abu Sebastian, Roland Mathis, Matteo Manica, Heiner Giefers, Tomas Tuma, Costas Bekas, Alessandro Curioni, Evangelos Eleftheriou
As CMOS scaling reaches its technological limits, a radical departure from traditional von Neumann systems, which involve separate processing and memory units, is needed in order to significantly extend the performance of today's computers.
Emerging Technologies
no code implementations • CAI (COLING) 2022 • Silvia Terragni, Bruna Guedes, Andre Manso, Modestas Filipavicius, Nghia Khau, Roland Mathis
Ideally TOD systems should be able to detect dialog breakdowns to prevent users from quitting a conversation and to encourage them to interact with the system again.
no code implementations • 20 Feb 2024 • Ivan Sekulić, Silvia Terragni, Victor Guimarães, Nghia Khau, Bruna Guedes, Modestas Filipavicius, André Ferreira Manso, Roland Mathis
Notably, we have observed that fine-tuning enhances the simulator's coherence with user goals, effectively mitigating hallucinations -- a major source of inconsistencies in simulator responses.