9 citations · 9 across the 2 of their papers we have counts for
3 papers
GRaSp: Automatic Example Optimization for In-Context Learning in Low-Data Tasks
Simen Bihaug-Frøyland, Henrik Brådland
In-context learning enables large language models to adapt to new tasks, but their performance is highly sensitive to the selected examples. Finding effective demonstrations is par…
Knowledge-Informed Automatic Feature Extraction via Collaborative Large Language Model Agents
Henrik Bradland, Morten Goodwin, Vladimir I. Zadorozhny +1
The performance of machine learning models on tabular data is critically dependent on high-quality feature engineering. While Large Language Models (LLMs) have shown promise in aut…
A New HOPE: Domain-agnostic Automatic Evaluation of Text Chunking
Henrik Brådland, Morten Goodwin, Per-Arne Andersen +2
Document chunking fundamentally impacts Retrieval-Augmented Generation (RAG) by determining how source materials are segmented before indexing. Despite evidence that Large Language…