A survey of large language models

WX Zhao, K Zhou, J Li, T Tang, X Wang, Y Hou… - arXiv preprint arXiv …, 2023 - arxiv.org
Language is essentially a complex, intricate system of human expressions governed by
grammatical rules. It poses a significant challenge to develop capable AI algorithms for …

Bloom: A 176b-parameter open-access multilingual language model

T Le Scao, A Fan, C Akiki, E Pavlick, S Ilić, D Hesslow… - 2023 - inria.hal.science
Large language models (LLMs) have been shown to be able to perform new tasks based on
a few demonstrations or natural language instructions. While these capabilities have led to …

Multilingual large language model: A survey of resources, taxonomy and frontiers

L Qin, Q Chen, Y Zhou, Z Chen, Y Li, L Liao… - arXiv preprint arXiv …, 2024 - arxiv.org
Multilingual Large Language Models are capable of using powerful Large Language
Models to handle and respond to queries in multiple languages, which achieves remarkable …

Investigating the translation performance of a large multilingual language model: the case of bloom

R Bawden, F Yvon - arXiv preprint arXiv:2303.01911, 2023 - arxiv.org
The NLP community recently saw the release of a new large open-access multilingual
language model, BLOOM (BigScience et al., 2022) covering 46 languages. We focus on …

CIF-Bench: A Chinese Instruction-Following Benchmark for Evaluating the Generalizability of Large Language Models

Y Li, G Zhang, X Qu, J Li, Z Li, Z Wang, H Li… - arXiv preprint arXiv …, 2024 - arxiv.org
The advancement of large language models (LLMs) has enhanced the ability to generalize
across a wide range of unseen natural language processing (NLP) tasks through instruction …

A deep learning-based intelligent quality detection model for machine translation

M Chen - IEEE Access, 2023 - ieeexplore.ieee.org
With more and more active international connections, the complex scenes-aware machine
translation has been a novel concern in the area of natural language processing. Although …

Disco: A large scale human annotated corpus for disfluency correction in indo-european languages

V Bhat, P Jyothi, P Bhattacharyya - arXiv preprint arXiv:2310.16749, 2023 - arxiv.org
Disfluency correction (DC) is the process of removing disfluent elements like fillers,
repetitions and corrections from spoken utterances to create readable and interpretable text …

Autocorrect in the process of translation--multi-task learning improves dialogue machine translation

T Wang, C Zhao, M Wang, L Li, D Xiong - arXiv preprint arXiv:2103.16189, 2021 - arxiv.org
Automatic translation of dialogue texts is a much needed demand in many real life
scenarios. However, the currently existing neural machine translation delivers unsatisfying …

Bloom: A 176b-parameter open-access multilingual language model

BS Workshop, TL Scao, A Fan, C Akiki… - arXiv preprint arXiv …, 2022 - arxiv.org
Large language models (LLMs) have been shown to be able to perform new tasks based on
a few demonstrations or natural language instructions. While these capabilities have led to …

The university of edinburgh-uppsala university's submission to the wmt 2020 chat translation task

N Moghe, C Hardmeier, R Bawden - Fifth Conference on …, 2020 - research.ed.ac.uk
This paper describes the joint submission of the University of Edinburgh and Uppsala
University to the WMT'20 chat translation task for both language directions (English↔ …