activity
20142024
most citedWhen Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

28 citations · 111 across the 13 of their papers we have counts for

collaborators

13 papers

cs.CL2024

Scaling Sign Language Translation

Biao Zhang, Garrett Tanzer, Orhan Firat

Sign language translation (SLT) addresses the problem of translating information from a sign language in video to a spoken language in text. Existing studies, while showing progres…

cs.CL202428 cited

When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Biao Zhang, Zhongtao Liu, Colin Cherry +1

While large language models (LLMs) often adopt finetuning to unlock their capabilities for downstream applications, our understanding on the inductive biases (especially the scalin…

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.CL202318 cited

Reinforced Self-Training (ReST) for Language Modeling

Caglar Gulcehre, Tom Le Paine, Srivatsan Srinivasan +11

Reinforcement learning from human feedback (RLHF) can improve the quality of large language model's (LLM) outputs by aligning them with human preferences. We propose a simple algor…

cs.CL20235 cited

The Devil is in the Errors: Leveraging Large Language Models for Fine-grained Machine Translation Evaluation

Patrick Fernandes, Daniel Deutsch, Mara Finkelstein +7

Automatic evaluation of machine translation (MT) is a critical tool driving the rapid iterative development of MT systems. While considerable progress has been made on estimating 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…