most citedThe unreasonable effectiveness of few-shot learning for machine translation

24 citations · 52 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL202310 cited

MADLAD-400: A Multilingual And Document-Level Large Audited Dataset

Sneha Kudugunta, Isaac Caswell, Biao Zhang +8

We introduce MADLAD-400, a manually audited, general domain 3T token monolingual dataset based on CommonCrawl, spanning 419 languages. We discuss the limitations revealed by self-a…

cs.CL20235 cited

Cross-Lingual Supervision improves Large Language Models Pre-training

Andrea Schioppa, Xavier Garcia, Orhan Firat

The recent rapid progress in pre-training Large Language Models has relied on using self-supervised language modeling objectives like next token prediction or span corruption. On t…

cs.CL20236 cited

UniMax: Fairer and more Effective Language Sampling for Large-Scale Multilingual Pretraining

Hyung Won Chung, Noah Constant, Xavier Garcia +4

Pretrained multilingual large language models have typically used heuristic temperature-based sampling to balance between different languages. However previous work has not systema…

cs.CL20235 cited

Scaling Laws for Multilingual Neural Machine Translation

Patrick Fernandes, Behrooz Ghorbani, Xavier Garcia +2

In this work, we provide a large-scale empirical study of the scaling properties of multilingual neural machine translation models. We examine how increases in the model size affec…

cs.CL202324 cited

The unreasonable effectiveness of few-shot learning for machine translation

Xavier Garcia, Yamini Bansal, Colin Cherry +5

We demonstrate the potential of few-shot translation systems, trained with unpaired language data, for both high and low-resource language pairs. We show that with only 5 examples…

cs.LG2023

Measuring The Impact Of Programming Language Distribution

Gabriel Orlanski, Kefan Xiao, Xavier Garcia +6

Current benchmarks for evaluating neural code models focus on only a small subset of programming languages, excluding many popular languages such as Go or Rust. To ameliorate this…