Search Results for author:
Found 4 papers, 2 papers with code
generAItor: Tree-in-the-Loop Text Generation for Language Model Explainability and Adaptation
Large language models (LLMs) are widely deployed in various downstream tasks, e. g., auto-completion, aided writing, or chat-based text generation.
Revealing the Unwritten: Visual Investigation of Beam Search Trees to Address Language Model Prompting Challenges
We quantitatively show the value of exposing the beam search tree and present five detailed analysis scenarios addressing the identified challenges.
explAIner: A Visual Analytics Framework for Interactive and Explainable Machine Learning
We propose a framework for interactive and explainable machine learning that enables users to (1) understand machine learning models; (2) diagnose model limitations using different explainable AI methods; as well as (3) refine and optimize the models.
BIG-bench Machine Learning
Explainable Artificial Intelligence (XAI)
Uncertainty-Aware Principal Component Analysis
We present a technique to perform dimensionality reduction on data that is subject to uncertainty.
