activity
20182022
most citedA Comparison of Techniques for Sentiment Classification of Film Reviews

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL2022

CrossAligner & Co: Zero-Shot Transfer Methods for Task-Oriented Cross-lingual Natural Language Understanding

Milan Gritta, Ruoyu Hu, Ignacio Iacobacci

Task-oriented personal assistants enable people to interact with a host of devices and services using natural language. One of the challenges of making neural dialogue systems avai…

cs.CL2021

XeroAlign: Zero-Shot Cross-lingual Transformer Alignment

Milan Gritta, Ignacio Iacobacci

The introduction of pretrained cross-lingual language models brought decisive improvements to multilingual NLP tasks. However, the lack of labelled task data necessitates a variety…

cs.CL2020

Conversation Graph: Data Augmentation, Training and Evaluation for Non-Deterministic Dialogue Management

Milan Gritta, Gerasimos Lampouras, Ignacio Iacobacci

Task-oriented dialogue systems typically rely on large amounts of high-quality training data or require complex handcrafted rules. However, existing datasets are often limited in s…

cs.CL20191 cited

A Comparison of Techniques for Sentiment Classification of Film Reviews

Milan Gritta

We undertake the task of comparing lexicon-based sentiment classification of film reviews with machine learning approaches. We look at existing methodologies and attempt to emulate…

cs.CL2018

A Pragmatic Guide to Geoparsing Evaluation

Milan Gritta, Mohammad Taher Pilehvar, Nigel Collier

Empirical methods in geoparsing have thus far lacked a standard evaluation framework describing the task, metrics and data used to compare state-of-the-art systems. Evaluation is f…