3 papers
cs.SE2025
ReadMe.LLM: A Framework to Help LLMs Understand Your Library
Sandya Wijaya, Jacob Bolano, Alejandro Gomez Soteres +3
Large Language Models (LLMs) often struggle with code generation tasks involving niche software libraries. Existing code generation techniques with only human-oriented documentatio…
cs.LG2024
Can Custom Models Learn In-Context? An Exploration of Hybrid Architecture Performance on In-Context Learning Tasks
Ryan Campbell, Nelson Lojo, Kesava Viswanadha +5
In-Context Learning (ICL) is a phenomenon where task learning occurs through a prompt sequence without the necessity of parameter updates. ICL in Multi-Headed Attention (MHA) with…
cs.LG2024
Polynomial Regression as a Task for Understanding In-context Learning Through Finetuning and Alignment
Max Wilcoxson, Morten Svendgård, Ria Doshi +3
Simple function classes have emerged as toy problems to better understand in-context-learning in transformer-based architectures used for large language models. But previously prop…