Search Results for author: Alon Lavie

Found 29 papers, 9 papers with code

QualityAdapt: an Automatic Dialogue Quality Estimation Framework

1 code implementation SIGDIAL (ACL) 2022 John Mendonca, Alon Lavie, Isabel Trancoso

Despite considerable advances in open-domain neural dialogue systems, their evaluation remains a bottleneck.

A Case Study on the Importance of Named Entities in a Machine Translation Pipeline for Customer Support Content

no code implementations EAMT 2022 Miguel Menezes, Vera Cabarrão, Pedro Mota, None Helena Moniz, Alon Lavie

This paper describes the research developed at Unbabel, a Portuguese Machine-translation start-up, that combines MT with human post-edition and focuses strictly on customer service content.

Machine Translation named-entity-recognition +2

Agent and User-Generated Content and its Impact on Customer Support MT

no code implementations EAMT 2022 Madalena Gonçalves, Marianna Buchicchio, Craig Stewart, Helena Moniz, Alon Lavie

This paper illustrates a new evaluation framework developed at Unbabel for measuring the quality of source language text and its effect on both Machine Translation (MT) and Human Post-Edition (PE) performed by non-professional post-editors.

Machine Translation Translation

Simple LLM Prompting is State-of-the-Art for Robust and Multilingual Dialogue Evaluation

1 code implementation31 Aug 2023 John Mendonça, Patrícia Pereira, Helena Moniz, João Paulo Carvalho, Alon Lavie, Isabel Trancoso

Despite significant research effort in the development of automatic dialogue evaluation metrics, little thought is given to evaluating dialogues other than in English.

Dialogue Evaluation

Towards Multilingual Automatic Dialogue Evaluation

1 code implementation31 Aug 2023 John Mendonça, Alon Lavie, Isabel Trancoso

The main limiting factor in the development of robust multilingual dialogue evaluation metrics is the lack of multilingual data and the limited availability of open sourced multilingual dialogue systems.

Dialogue Evaluation Machine Translation +1

The Inside Story: Towards Better Understanding of Machine Translation Neural Evaluation Metrics

1 code implementation19 May 2023 Ricardo Rei, Nuno M. Guerreiro, Marcos Treviso, Luisa Coheur, Alon Lavie, André F. T. Martins

Neural metrics for machine translation evaluation, such as COMET, exhibit significant improvements in their correlation with human judgments, as compared to traditional metrics based on lexical overlap, such as BLEU.

Decision Making Machine Translation +2

Appropriateness is all you need!

no code implementations27 Apr 2023 Hendrik Kempt, Alon Lavie, Saskia K. Nagel

In answering this limitation, in this paper we argue for limiting chatbots in the range of topics they can chat about according to the normative concept of appropriateness.

Chatbot

MT-Telescope: An interactive platform for contrastive evaluation of MT systems

no code implementations ACL 2021 Ricardo Rei, Ana C Farinha, Craig Stewart, Luisa Coheur, Alon Lavie

We present MT-Telescope, a visualization platform designed to facilitate comparative analysis of the output quality of two Machine Translation (MT) systems.

Machine Translation Translation

Unbabel's Participation in the WMT20 Metrics Shared Task

1 code implementation29 Oct 2020 Ricardo Rei, Craig Stewart, Catarina Farinha, Alon Lavie

Overall, our systems achieve strong results for all language pairs on previous test sets and in many cases set a new state-of-the-art.

COMET: A Neural Framework for MT Evaluation

1 code implementation EMNLP 2020 Ricardo Rei, Craig Stewart, Ana C Farinha, Alon Lavie

We present COMET, a neural framework for training multilingual machine translation evaluation models which obtains new state-of-the-art levels of correlation with human judgements.

Language Modelling Machine Translation +1

Locally Non-Linear Learning for Statistical Machine Translation via Discretization and Structured Regularization

no code implementations TACL 2014 Jonathan H. Clark, Chris Dyer, Alon Lavie

Linear models, which support efficient learning and inference, are the workhorses of statistical machine translation; however, linear decision rules are less attractive from a modeling perspective.

Feature Engineering Language Modelling +3

Cannot find the paper you are looking for? You can Submit a new open access paper.