DAT generates query-specific in-context translation examples using only an LLM, improving English-to-low-resource translation over zero-shot in most tested languages.
compare-mt: A Tool for Holistic Comparison of Language Generation Systems
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abstract
In this paper, we describe compare-mt, a tool for holistic analysis and comparison of the results of systems for language generation tasks such as machine translation. The main goal of the tool is to give the user a high-level and coherent view of the salient differences between systems that can then be used to guide further analysis or system improvement. It implements a number of tools to do so, such as analysis of accuracy of generation of particular types of words, bucketed histograms of sentence accuracies or counts based on salient characteristics, and extraction of characteristic $n$-grams for each system. It also has a number of advanced features such as use of linguistic labels, source side data, or comparison of log likelihoods for probabilistic models, and also aims to be easily extensible by users to new types of analysis. The code is available at https://github.com/neulab/compare-mt
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cs.CL 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
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Exploring In-context Example Generation for Machine Translation
DAT generates query-specific in-context translation examples using only an LLM, improving English-to-low-resource translation over zero-shot in most tested languages.