1 citations · 1 across the 4 of their papers we have counts for
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Retrieval-Augmented Machine Translation with Unstructured Knowledge
Jiaan Wang, Fandong Meng, Yingxue Zhang +1
Retrieval-augmented generation (RAG) introduces additional information to enhance large language models (LLMs). In machine translation (MT), previous work typically retrieves in-co…
CRAT: A Multi-Agent Framework for Causality-Enhanced Reflective and Retrieval-Augmented Translation with Large Language Models
Meiqi Chen, Fandong Meng, Yingxue Zhang +2
Large language models (LLMs) have shown great promise in machine translation, but they still struggle with contextually dependent terms, such as new or domain-specific words. This…
TEAL: Tokenize and Embed ALL for Multi-modal Large Language Models
Zhen Yang, Yingxue Zhang, Fandong Meng +1
Despite Multi-modal Large Language Models (MM-LLMs) have made exciting strides recently, they are still struggling to efficiently model the interactions among multi-modal inputs an…
Findings of the WMT 2022 Shared Task on Translation Suggestion
Zhen Yang, Fandong Meng, Yingxue Zhang +2
We report the result of the first edition of the WMT shared task on Translation Suggestion (TS). The task aims to provide alternatives for specific words or phrases given the entir…
WeTS: A Benchmark for Translation Suggestion
Zhen Yang, Fandong Meng, Yingxue Zhang +2
Translation Suggestion (TS), which provides alternatives for specific words or phrases given the entire documents translated by machine translation (MT) \cite{lee2021intellicat}, h…