3 papers
cs.CL2025
Refract ICL: Rethinking Example Selection in the Era of Million-Token Models
Arjun R. Akula, Kazuma Hashimoto, Krishna Srinivasan +3
The emergence of long-context large language models (LLMs) has enabled the use of hundreds, or even thousands, of demonstrations for in-context learning (ICL) - a previously imprac…
cs.CL2023
It's All Relative! -- A Synthetic Query Generation Approach for Improving Zero-Shot Relevance Prediction
Aditi Chaudhary, Karthik Raman, Michael Bendersky
Recent developments in large language models (LLMs) have shown promise in their ability to generate synthetic query-document pairs by prompting with as few as 8 demonstrations. Thi…
cs.CL2023
Crossing the Threshold: Idiomatic Machine Translation through Retrieval Augmentation and Loss Weighting
Emmy Liu, Aditi Chaudhary, Graham Neubig
Idioms are common in everyday language, but often pose a challenge to translators because their meanings do not follow from the meanings of their parts. Despite significant advance…