Learning compact metrics for mt
NettetMT (Barrault et al.,2024). While an increased research interest in neural methods for training MT models and systems has resulted in a recent, dramatic improvement in MT quality, MT evaluation has fallen behind. The MT research community still relies largely on outdated metrics and no new, widely-adopted standard has emerged. Nettet(Lin and Och, 2004) recently proposed a set of metrics (ROUGE) for MT evaluation. ROUGE-L is a longest commonsubsequence (LCS)basedautomatic evaluation metric for MT. The intuition behind it is that long common subsequences reect a large over- lap between a candidate translation and a reference translation.
Learning compact metrics for mt
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NettetRecent developments in machine translation and multilingual text generation have led researchers to adopt trained metrics such as COMET or BLEURT, which treat … Nettet12. okt. 2024 · Title: Learning Compact Metrics for MT; ... Multilingual Multimodal Learning with Machine Translated Text [27.7207234512674] 英語のマルチモーダル …
Nettet1. jan. 2015 · Learning a proper distance metric is of vital importance for many distance based applications. Distance metric learning aims to learn a set of latent factors based on which the distances between data points can be effectively measured. The number of latent factors incurs a tradeoff: a small amount of factors are not powerful and … Nettet8. okt. 2024 · The quality of machine translation systems has dramatically improved over the last decade, and as a result, evaluation has become an increasingly challenging …
Nettet1. jan. 2024 · Request PDF On Jan 1, 2024, Amy Pu and others published Learning Compact Metrics for MT Find, read and cite all the research you need on ResearchGate NettetLearning Compact Metrics for MT. In Marie-Francine Moens , Xuanjing Huang , Lucia Specia , Scott Wen-tau Yih , editors, Proceedings of the 2024 Conference on Empirical …
Nettet1. sep. 2024 · Abstract. Automatic Machine Translation (MT) evaluation is an active field of research, with a handful of new metrics devised every year. Evaluation metrics are generally benchmarked against manual assessment of translation quality, with performance measured in terms of overall correlation with human scores. Much work …
NettetRecent developments in machine translation and multilingual text generation have led researchers to adopt trained metrics such as COMET or BLEURT, which treat … edge hill merchNettetRecent developments in machine translation and multilingual text generation have led researchers to adopt trained metrics such as COMET or BLEURT, which treat evaluation as a regression problem and use representations from multilingual pre-trained models such as XLM-RoBERTa or mBERT. Yet studies on related tasks suggest that these models … edgehill meridianNettetRecent developments in machine translation and multilingual text generation have led researchers to adopt trained metrics such as COMET or BLEURT, ... Learning Compact Metrics for MT. 2024-10-12 20:39:35 Amy Pu, Hyung Won Chung, Ankur P. Parikh, Sebastian Gehrmann, ... congee herbsNettet30. des. 2014 · The most prominent metrics in the field are BLEU (Papineni et al. 2002) and METEOR (Banerjee and Lavie 2005). Even though these metrics are extensively used in MT research, scientists... congee masterNettetTitle: Learning Compact Metrics for MT; Authors: Amy Pu, Hyung Won Chung, Ankur P. Parikh, Sebastian Gehrmann, Thibault Sellam; ... XLST: Cross-lingual Self-training to … congee instant pot ground beefNettet31. mar. 2024 · pu-etal-2024-learning. Cite (ACL): Amy Pu, Hyung Won Chung, Ankur Parikh, Sebastian Gehrmann, and Thibault Sellam. 2024. Learning Compact Metrics … congee molly yehNettet7. apr. 2024 · Abstract:Metric learning networks are used to compute image embeddings, which are widely used in many applications such as image retrieval and face recognition. In this paper, we propose to use network distillation to efficiently compute image embeddings with small networks. Network distillation has been edgehill microsoft 365