Search Results for author:
Found 32 papers, 11 papers with code
Naver Labs Europe’s Participation in the Robustness, Chat, and Biomedical Tasks at WMT 2020
This paper describes Naver Labs Europe’s participation in the Robustness, Chat, and Biomedical Translation tasks at WMT 2020.
Zero-Shot Aspect-Based Scientific Document Summarization using Self-Supervised Pre-training
We study the zero-shot setting for the aspect-based scientific document summarization task.
Findings of the WMT Shared Task on Machine Translation Using Terminologies
Language domains that require very careful use of terminology are abundant and reflect a significant part of the translation industry.
Visualizing Cross‐Lingual Discourse Relations in Multilingual TED Corpora
This paper presents an interactive data dashboard that provides users with an overview of the preservation of discourse relations among 28 language pairs.
Zero-shot cross-lingual transfer in instruction tuning of large language models
Instruction tuning (IT) is widely used to teach pretrained large language models (LLMs) to follow arbitrary instructions, but is under-studied in multilingual settings.
Key ingredients for effective zero-shot cross-lingual knowledge transfer in generative tasks
Previous works notice a frequent problem of generation in a wrong language and propose approaches to address it, usually using mT5 as a backbone model.
Multilingual DistilWhisper: Efficient Distillation of Multi-task Speech Models via Language-Specific Experts
Whisper is a multitask and multilingual speech model covering 99 languages.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Empirical study of pretrained multilingual language models for zero-shot cross-lingual knowledge transfer in generation
Zero-shot cross-lingual knowledge transfer enables the multilingual pretrained language model (mPLM), finetuned on a task in one language, make predictions for this task in other languages.
Long-Tail Theory under Gaussian Mixtures
We suggest a simple Gaussian mixture model for data generation that complies with Feldman's long tail theory (2020).
BLOOM+1: Adding Language Support to BLOOM for Zero-Shot Prompting
We find language adaptation to be effective at improving zero-shot performance in new languages.
Memory-efficient NLLB-200: Language-specific Expert Pruning of a Massively Multilingual Machine Translation Model
The recently released NLLB-200 is a set of multilingual Neural Machine Translation models that cover 202 languages.
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions.
SMaLL-100: Introducing Shallow Multilingual Machine Translation Model for Low-Resource Languages
In recent years, multilingual machine translation models have achieved promising performance on low-resource language pairs by sharing information between similar languages, thus enabling zero-shot translation.
What Do Compressed Multilingual Machine Translation Models Forget?
In this work, we assess the impact of compression methods on Multilingual Neural Machine Translation models (MNMT) for various language groups, gender, and semantic biases by extensive analysis of compressed models on different machine translation benchmarks, i. e. FLORES-101, MT-Gender, and DiBiMT.
DaLC: Domain Adaptation Learning Curve Prediction for Neural Machine Translation
Domain Adaptation (DA) of Neural Machine Translation (NMT) model often relies on a pre-trained general NMT model which is adapted to the new domain on a sample of in-domain parallel data.
Adapting BigScience Multilingual Model to Unseen Languages
We benchmark different strategies of adding new languages (German and Korean) into the BigScience's pretrained multilingual language model with 1. 3 billion parameters that currently supports 13 languages.
Zero-Shot and Few-Shot Classification of Biomedical Articles in Context of the COVID-19 Pandemic
MeSH (Medical Subject Headings) is a large thesaurus created by the National Library of Medicine and used for fine-grained indexing of publications in the biomedical domain.
Speeding Up Entmax
Softmax is the de facto standard in modern neural networks for language processing when it comes to normalizing logits.
Multilingual Domain Adaptation for NMT: Decoupling Language and Domain Information with Adapters
In this work we study the compositionality of language and domain adapters in the context of Machine Translation.
Efficient Inference for Multilingual Neural Machine Translation
Multilingual NMT has become an attractive solution for MT deployment in production.
On the Evaluation of Machine Translation for Terminology Consistency
As neural machine translation (NMT) systems become an important part of professional translator pipelines, a growing body of work focuses on combining NMT with terminologies.
Do Multilingual Neural Machine Translation Models Contain Language Pair Specific Attention Heads?
Recent studies on the analysis of the multilingual representations focus on identifying whether there is an emergence of language-independent representations, or whether a multilingual model partitions its weights among different languages.
The Rediscovery Hypothesis: Language Models Need to Meet Linguistics
In this paper, we study whether linguistic knowledge is a necessary condition for the good performance of modern language models, which we call the \textit{rediscovery hypothesis}.
A Multilingual Neural Machine Translation Model for Biomedical Data
We release a multilingual neural machine translation model, which can be used to translate text in the biomedical domain.
Machine Translation of Restaurant Reviews: New Corpus for Domain Adaptation and Robustness
We share a French-English parallel corpus of Foursquare restaurant reviews (https://europe. naverlabs. com/research/natural-language-processing/machine-translation-of-restaurant-reviews), and define a new task to encourage research on Neural Machine Translation robustness and domain adaptation, in a real-world scenario where better-quality MT would be greatly beneficial.
On the use of BERT for Neural Machine Translation
Exploiting large pretrained models for various NMT tasks have gained a lot of visibility recently.
Aspect Based Sentiment Analysis into the Wild
In this paper, we test state-of-the-art Aspect Based Sentiment Analysis (ABSA) systems trained on a widely used dataset on actual data.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
