Arnon Amir, Michael Lindenbaum
IEEE Transactions on Pattern Analysis and Machine Intelligence
This paper proposes a new type of transfer system, called Similarity-driven Transfer System (or SimTran), which uses an example-based approach to the transfer phase of MT. In this paper, we describe a method for calculating similarity, a method for searching the most appropriate set of translation rules, and a method for constructing an output structure from those selected rules. Further, we show that SimTran can use not only translation examples but also syntax-based translation rules used in conventional transfer systems at the same time.
Arnon Amir, Michael Lindenbaum
IEEE Transactions on Pattern Analysis and Machine Intelligence
Kellen Cheng, Anna Lisa Gentile, et al.
EMNLP 2024
Ismail Akhalwaya, Shashanka Ubaru, et al.
ICLR 2024
Amy Lin, Sujit Roy, et al.
AGU 2024