2 papers
cs.CL2024
CALICO: Conversational Agent Localization via Synthetic Data Generation
Andy Rosenbaum, Pegah Kharazmi, Ershad Banijamali +8
We present CALICO, a method to fine-tune Large Language Models (LLMs) to localize conversational agent training data from one language to another. For slots (named entities), CALIC…
cs.CL2024
When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model Leaderboards
Norah Alzahrani, Hisham Abdullah Alyahya, Yazeed Alnumay +9
Large Language Model (LLM) leaderboards based on benchmark rankings are regularly used to guide practitioners in model selection. Often, the published leaderboard rankings are take…