activity
20222024
most citedPrompting Large Language Model for Machine Translation: A Case Study

68 citations · 142 across the 7 of their papers we have counts for

collaborators

7 papers

cs.AI20243 cited

Direct Language Model Alignment from Online AI Feedback

Shangmin Guo, Biao Zhang, Tianlin Liu +9

Direct alignment from preferences (DAP) methods, such as DPO, have recently emerged as efficient alternatives to reinforcement learning from human feedback (RLHF), that do not requ…

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.CL202314 cited

SLTUNET: A Simple Unified Model for Sign Language Translation

Biao Zhang, Mathias Müller, Rico Sennrich

Despite recent successes with neural models for sign language translation (SLT), translation quality still lags behind spoken languages because of the data scarcity and modality ga…

cs.CL2023

Efficient CTC Regularization via Coarse Labels for End-to-End Speech Translation

Biao Zhang, Barry Haddow, Rico Sennrich

For end-to-end speech translation, regularizing the encoder with the Connectionist Temporal Classification (CTC) objective using the source transcript or target translation as labe…

cs.CL202368 cited

Prompting Large Language Model for Machine Translation: A Case Study

Biao Zhang, Barry Haddow, Alexandra Birch

Research on prompting has shown excellent performance with little or even no supervised training across many tasks. However, prompting for machine translation is still under-explor…