Recent advances in retrieval-augmented models for image captioning highlight the benefit
of retrieving related captions for efficient, lightweight models with strong domain-transfer …

This paper rethinks translation memory augmented neural machine translation (TM-
augmented NMT) from two perspectives, ie, a probabilistic view of retrieval and the variance …

This paper explores Memory-Augmented Neural Networks (MANNs), delving into how they
blend human-like memory processes into AI. It covers different memory types, like sensory …

Retrieval-Augmented Machine Translation (RAMT) is attracting growing attention. This is
because RAMT not only improves translation metrics, but is also assumed to implement …

Retrieval-augmented generation (RAG) introduces additional information to enhance large
language models (LLMs). In machine translation (MT), previous work typically retrieves in …

Retrieval-augmented machine translation leverages examples from a translation memory by
retrieving similar instances. These examples are used to condition the predictions of a …

While large language models (LLMs) pre-trained on massive amounts of unpaired language
data have reached the state-of-the-art in machine translation (MT) of general domain texts …

The success of pre-trained language models (PLMs) in language understanding tasks has
attracted attention to these models being applied as building blocks in information retrieval …

La traduction neuronale à partir d'exemples s' appuie sur l'exploitation d'une mémoire de
traduction contenant des exemples similaires aux phrases à traduire. Ces exemples sont …