112 citations · 112 across the 2 of their papers we have counts for
2 papers
cs.LG2025
OptiSeq: Ordering Examples On-The-Fly for In-Context Learning
Rahul Atul Bhope, Praveen Venkateswaran, K. R. Jayaram +3
Developers using LLMs and LLM-based agents in their applications have provided plenty of anecdotal evidence that in-context-learning (ICL) is fragile. In this paper, we show that i…
cs.CL2022★ 112 cited
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…