Leveraging Explanations in Interactive Machine Learning: An Overview

Leveraging Explanations in Interactive Machine Learning: An Overview

29 July 2022

Wolfgang Stammer

Elizabeth M. Daly

Papers citing "Leveraging Explanations in Interactive Machine Learning: An Overview"

16 / 16 papers shown

Title
Exploring the Impact of Explainable AI and Cognitive Capabilities on Users' Decisions Federico Maria Cau Lucio Davide Spano 24 0 0 02 May 2025
If Concept Bottlenecks are the Question, are Foundation Models the Answer? Nicola Debole Pietro Barbiero Francesco Giannini Andrea Passerini Stefano Teso Emanuele Marconato 62 0 0 28 Apr 2025
Shortcuts and Identifiability in Concept-based Models from a Neuro-Symbolic Lens Samuele Bortolotti Emanuele Marconato Paolo Morettin Andrea Passerini Stefano Teso 53 2 0 16 Feb 2025
Representation Debiasing of Generated Data Involving Domain Experts Aditya Bhattacharya Simone Stumpf K. Verbert 21 2 0 17 May 2024
Learning To Guide Human Decision Makers With Vision-Language Models Debodeep Banerjee Stefano Teso Burcu Sayin Andrea Passerini 32 1 0 25 Mar 2024
Unpacking Human-AI interactions: From interaction primitives to a design space Konstantinos Tsiakas Dave Murray-Rust 19 3 0 10 Jan 2024
One Explanation Does Not Fit XIL Felix Friedrich David Steinmann Kristian Kersting LRM 32 2 0 14 Apr 2023
Right for the Right Latent Factors: Debiasing Generative Models via Disentanglement Xiaoting Shao Karl Stelzner Kristian Kersting CML DRL 22 3 0 01 Feb 2022
Interactive Disentanglement: Learning Concepts by Interacting with their Prototype Representations Wolfgang Stammer Marius Memmel P. Schramowski Kristian Kersting 76 25 0 04 Dec 2021
Editing a classifier by rewriting its prediction rules Shibani Santurkar Dimitris Tsipras Mahalaxmi Elango David Bau Antonio Torralba A. Madry KELM 175 89 0 02 Dec 2021
A Survey on Cost Types, Interaction Schemes, and Annotator Performance Models in Selection Algorithms for Active Learning in Classification M. Herde Denis Huseljic Bernhard Sick A. Calma 29 25 0 23 Sep 2021
On Interactive Machine Learning and the Potential of Cognitive Feedback C. J. Michael Dina M. Acklin J. Scheuerman 15 12 0 23 Mar 2020
A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras S. Laine Timo Aila 262 10,183 0 12 Dec 2018
e-SNLI: Natural Language Inference with Natural Language Explanations Oana-Maria Camburu Tim Rocktaschel Thomas Lukasiewicz Phil Blunsom LRM 252 618 0 04 Dec 2018
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,231 0 24 Jun 2017
Learning Certifiably Optimal Rule Lists for Categorical Data E. Angelino Nicholas Larus-Stone Daniel Alabi Margo Seltzer Cynthia Rudin 46 196 0 06 Apr 2017