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A comprehensive overview of large language models
Large Language Models (LLMs) have recently demonstrated remarkable capabilities in
natural language processing tasks and beyond. This success of LLMs has led to a large …
natural language processing tasks and beyond. This success of LLMs has led to a large …
Palm: Scaling language modeling with pathways
Large language models have been shown to achieve remarkable performance across a
variety of natural language tasks using few-shot learning, which drastically reduces the …
variety of natural language tasks using few-shot learning, which drastically reduces the …
Findings of the 2019 conference on machine translation (WMT19)
L Barrault, O Bojar, MR Costa-Jussa, C Federmann… - 2019 - zora.uzh.ch
This paper presents the results of the premier shared task organized alongside the
Conference on Machine Translation (WMT) 2019. Participants were asked to build machine …
Conference on Machine Translation (WMT) 2019. Participants were asked to build machine …
Survey of low-resource machine translation
We present a survey covering the state of the art in low-resource machine translation (MT)
research. There are currently around 7,000 languages spoken in the world and almost all …
research. There are currently around 7,000 languages spoken in the world and almost all …
Using natural language prompts for machine translation
We explore the use of natural language prompts for controlling various aspects of the
outputs generated by machine translation models. We demonstrate that natural language …
outputs generated by machine translation models. We demonstrate that natural language …
Better document-level machine translation with Bayes' rule
We show that Bayes' rule provides an effective mechanism for creating document translation
models that can be learned from only parallel sentences and monolingual documents a …
models that can be learned from only parallel sentences and monolingual documents a …
Transcormer: Transformer for sentence scoring with sliding language modeling
Sentence scoring aims at measuring the likelihood score of a sentence and is widely used in
many natural language processing scenarios, like reranking, which is to select the best …
many natural language processing scenarios, like reranking, which is to select the best …
Findings of the third workshop on neural generation and translation
This document describes the findings of the Third Workshop on Neural Generation and
Translation, held in concert with the annual conference of the Empirical Methods in Natural …
Translation, held in concert with the annual conference of the Empirical Methods in Natural …
WeChat neural machine translation systems for WMT20
We participate in the WMT 2020 shared news translation task on Chinese to English. Our
system is based on the Transformer (Vaswani et al., 2017a) with effective variants and the …
system is based on the Transformer (Vaswani et al., 2017a) with effective variants and the …
Uncertainty determines the adequacy of the mode and the tractability of decoding in sequence-to-sequence models
In many natural language processing (NLP) tasks the same input (eg source sentence) can
have multiple possible outputs (eg translations). To analyze how this ambiguity (also known …
have multiple possible outputs (eg translations). To analyze how this ambiguity (also known …