715 citations · 915 across the 10 of their papers we have counts for
4 papers · 1 filter
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…
Leveraging Large Language Models for Multiple Choice Question Answering
Joshua Robinson, Christopher Michael Rytting, David Wingate
While large language models (LLMs) like GPT-3 have achieved impressive results on multiple choice question answering (MCQA) tasks in the zero, one, and few-shot settings, they gene…
An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels
Taylor Sorensen, Joshua Robinson, Christopher Michael Rytting +6
Pre-trained language models derive substantial linguistic and factual knowledge from the massive corpora on which they are trained, and prompt engineering seeks to align these mode…
Leveraging the Inductive Bias of Large Language Models for Abstract Textual Reasoning
Christopher Michael Rytting, David Wingate
Large natural language models (such as GPT-3 or T5) demonstrate impressive abilities across a range of general NLP tasks. Here, we show that the knowledge embedded in such models p…