Papers by Max Wild

1 papers
Simul-LLM: A Framework for Exploring High-Quality Simultaneous Translation with Large Language Models (2024.acl-long)

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Challenge: Modern large language models (LLMs) contain billions of parameters and can perform a variety of downstream tasks.
Approach: They propose an open-source framework for fine-tuning large language models (LLMs) they address key challenges facing LLMs fine- tuned for simultaneous translation .
Outcome: The proposed framework validates classical SimulMT concepts and practices in the context of LLMs and explores adapting LLM fine-tuned for NMT to the task of Simul-LLM.

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