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Found 3 papers, 1 papers with code
Going Beyond Word Matching: Syntax Improves In-context Example Selection for Machine Translation
In-context learning (ICL) is the trending prompting strategy in the era of large language models (LLMs), where a few examples are demonstrated to evoke LLMs' power for a given task.
Ungrammatical-syntax-based In-context Example Selection for Grammatical Error Correction
In this paper, we propose a novel ungrammatical-syntax-based in-context example selection strategy for GEC.
Are Pre-trained Language Models Useful for Model Ensemble in Chinese Grammatical Error Correction?
To this end, we explore several ensemble strategies based on strong PLMs with four sophisticated single models.
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