Allowing humans to interactively guide machines where to look does not always improve human-AI team's classification accuracy

8 April 2024

Papers citing "Allowing humans to interactively guide machines where to look does not always improve human-AI team's classification accuracy"

6 / 6 papers shown

Title
Interactivity x Explainability: Toward Understanding How Interactivity Can Improve Computer Vision Explanations Indu Panigrahi Sunnie S. Y. Kim Amna Liaqat Rohan Jinturkar Olga Russakovsky Ruth C. Fong Parastoo Abtahi FAtt HAI 52 0 0 14 Apr 2025
Rethinking Interpretability in the Era of Large Language Models Chandan Singh J. Inala Michel Galley Rich Caruana Jianfeng Gao LRM AI4CE 75 60 0 30 Jan 2024
An Interactive UI to Support Sensemaking over Collections of Parallel Texts Joyce Zhou Elena L. Glassman Daniel S. Weld 26 1 0 11 Mar 2023
Post-hoc Concept Bottleneck Models Mert Yuksekgonul Maggie Wang James Y. Zou 133 183 0 31 May 2022
HIVE: Evaluating the Human Interpretability of Visual Explanations Sunnie S. Y. Kim Nicole Meister V. V. Ramaswamy Ruth C. Fong Olga Russakovsky 58 114 0 06 Dec 2021
Human-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AI Dakuo Wang Justin D. Weisz Michael J. Muller Parikshit Ram Werner Geyer Casey Dugan Y. Tausczik Horst Samulowitz Alexander G. Gray 166 309 0 05 Sep 2019