2 citations · 3 across the 3 of their papers we have counts for
3 papers
LLM Reasoning for Machine Translation: Synthetic Data Generation over Thinking Tokens
Armel Zebaze, Rachel Bawden, Benoît Sagot
Large reasoning models (LRMs) have led to new possibilities in terms of problem-solving, through the devising of a natural language thought process prior to answering a query. Whil…
In-Context Example Selection via Similarity Search Improves Low-Resource Machine Translation
Armel Zebaze, Benoît Sagot, Rachel Bawden
The ability of generative large language models (LLMs) to perform in-context learning has given rise to a large body of research into how best to prompt models for various natural…
Astraios: Parameter-Efficient Instruction Tuning Code Large Language Models
Terry Yue Zhuo, Armel Zebaze, Nitchakarn Suppattarachai +4
The high cost of full-parameter fine-tuning (FFT) of Large Language Models (LLMs) has led to a series of parameter-efficient fine-tuning (PEFT) methods. However, it remains unclear…