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BLEURT Has Universal Translations: An Analysis of Automatic Metrics by
  Minimum Risk Training
v1v2 (latest)

BLEURT Has Universal Translations: An Analysis of Automatic Metrics by Minimum Risk Training

Annual Meeting of the Association for Computational Linguistics (ACL), 2023
6 July 2023
Yiming Yan
Tao Wang
Chengqi Zhao
Shujian Huang
Jiajun Chen
Mingxuan Wang
ArXiv (abs)PDFHTMLGithub

Papers citing "BLEURT Has Universal Translations: An Analysis of Automatic Metrics by Minimum Risk Training"

18 / 18 papers shown
Title
From Internal Representations to Text Quality: A Geometric Approach to LLM Evaluation
From Internal Representations to Text Quality: A Geometric Approach to LLM Evaluation
Viacheslav Yusupov
Danil Maksimov
Ameliia Alaeva
Anna Vasileva
Anna Antipina
Tatyana Zaitseva
Alina Ermilova
Evgeny Burnaev
Egor Shvetsov
101
0
0
29 Sep 2025
Document-Level Text Generation with Minimum Bayes Risk Decoding using Optimal Transport
Document-Level Text Generation with Minimum Bayes Risk Decoding using Optimal TransportAnnual Meeting of the Association for Computational Linguistics (ACL), 2025
Yuu Jinnai
OT
171
0
0
29 May 2025
You Cannot Feed Two Birds with One Score: the Accuracy-Naturalness Tradeoff in Translation
You Cannot Feed Two Birds with One Score: the Accuracy-Naturalness Tradeoff in Translation
Gergely Flamich
David Vilar
Jan-Thorsten Peter
Markus Freitag
226
5
0
31 Mar 2025
OpeNLGauge: An Explainable Metric for NLG Evaluation with Open-Weights LLMs
OpeNLGauge: An Explainable Metric for NLG Evaluation with Open-Weights LLMs
Ivan Kartáč
Mateusz Lango
Ondrej Dusek
ELM
323
5
0
14 Mar 2025
Adding Chocolate to Mint: Mitigating Metric Interference in Machine Translation
Adding Chocolate to Mint: Mitigating Metric Interference in Machine Translation
José P. Pombal
Nuno M. Guerreiro
Ricardo Rei
André F. T. Martins
365
5
0
11 Mar 2025
SELU: Self-Learning Embodied MLLMs in Unknown Environments
SELU: Self-Learning Embodied MLLMs in Unknown Environments
Boyu Li
Haobin Jiang
Haobin Jiang
Weishuai Zeng
Haoran Li
Dongbin Zhao
Zongqing Lu
LRM
170
6
0
04 Oct 2024
Is Preference Alignment Always the Best Option to Enhance LLM-Based
  Translation? An Empirical Analysis
Is Preference Alignment Always the Best Option to Enhance LLM-Based Translation? An Empirical AnalysisConference on Machine Translation (WMT), 2024
Hippolyte Gisserot-Boukhlef
Ricardo Rei
Emmanuel Malherbe
C´eline Hudelot
Pierre Colombo
Nuno M. Guerreiro
191
5
0
30 Sep 2024
Unveiling the Power of Source: Source-based Minimum Bayes Risk Decoding for Neural Machine Translation
Unveiling the Power of Source: Source-based Minimum Bayes Risk Decoding for Neural Machine Translation
Boxuan Lyu
Hidetaka Kamigaito
Kotaro Funakoshi
Manabu Okumura
511
0
0
17 Jun 2024
Measuring Retrieval Complexity in Question Answering Systems
Measuring Retrieval Complexity in Question Answering Systems
Matteo Gabburo
Nicolaas Paul Jedema
Siddhant Garg
Leonardo F. R. Ribeiro
Alessandro Moschitti
160
2
0
05 Jun 2024
QUEST: Quality-Aware Metropolis-Hastings Sampling for Machine
  Translation
QUEST: Quality-Aware Metropolis-Hastings Sampling for Machine Translation
Gonccalo R. A. Faria
Sweta Agrawal
António Farinhas
Ricardo Rei
José G. C. de Souza
André F. T. Martins
185
7
0
28 May 2024
Can Automatic Metrics Assess High-Quality Translations?
Can Automatic Metrics Assess High-Quality Translations?
Sweta Agrawal
António Farinhas
Ricardo Rei
André F. T. Martins
155
15
0
28 May 2024
Enabling Weak LLMs to Judge Response Reliability via Meta Ranking
Enabling Weak LLMs to Judge Response Reliability via Meta Ranking
Zijun Liu
Boqun Kou
Peng Li
Ming Yan
Ji Zhang
Fei Huang
Yang Liu
258
7
0
19 Feb 2024
Improving Machine Translation with Human Feedback: An Exploration of
  Quality Estimation as a Reward Model
Improving Machine Translation with Human Feedback: An Exploration of Quality Estimation as a Reward ModelNorth American Chapter of the Association for Computational Linguistics (NAACL), 2024
Zhiwei He
Xing Wang
Wenxiang Jiao
Zhuosheng Zhang
Rui Wang
Shuming Shi
Zhaopeng Tu
ALM
308
34
0
23 Jan 2024
Lost in the Source Language: How Large Language Models Evaluate the
  Quality of Machine Translation
Lost in the Source Language: How Large Language Models Evaluate the Quality of Machine TranslationAnnual Meeting of the Association for Computational Linguistics (ACL), 2024
Xu Huang
Zhirui Zhang
Xiang Geng
Yichao Du
Jiajun Chen
Shujian Huang
172
17
0
12 Jan 2024
Robustness Tests for Automatic Machine Translation Metrics with
  Adversarial Attacks
Robustness Tests for Automatic Machine Translation Metrics with Adversarial AttacksConference on Empirical Methods in Natural Language Processing (EMNLP), 2023
Yichen Huang
Timothy Baldwin
185
3
0
01 Nov 2023
Quality-Aware Translation Models: Efficient Generation and Quality
  Estimation in a Single Model
Quality-Aware Translation Models: Efficient Generation and Quality Estimation in a Single ModelAnnual Meeting of the Association for Computational Linguistics (ACL), 2023
Christian Tomani
David Vilar
Markus Freitag
Colin Cherry
Subhajit Naskar
Mara Finkelstein
Xavier Garcia
Daniel Cremers
260
8
0
10 Oct 2023
Mitigating Hallucinations and Off-target Machine Translation with
  Source-Contrastive and Language-Contrastive Decoding
Mitigating Hallucinations and Off-target Machine Translation with Source-Contrastive and Language-Contrastive DecodingConference of the European Chapter of the Association for Computational Linguistics (EACL), 2023
Rico Sennrich
Jannis Vamvas
Alireza Mohammadshahi
HILM
437
51
0
13 Sep 2023
Automatically Correcting Large Language Models: Surveying the landscape
  of diverse self-correction strategies
Automatically Correcting Large Language Models: Surveying the landscape of diverse self-correction strategies
Liangming Pan
Michael Stephen Saxon
Wenda Xu
Deepak Nathani
Xinyi Wang
William Yang Wang
KELMLRM
379
264
0
06 Aug 2023
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