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2001.09219
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Explainable Active Learning (XAL): An Empirical Study of How Local Explanations Impact Annotator Experience
24 January 2020
Bhavya Ghai
Q. V. Liao
Yunfeng Zhang
Rachel K. E. Bellamy
Klaus Mueller
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Papers citing
"Explainable Active Learning (XAL): An Empirical Study of How Local Explanations Impact Annotator Experience"
10 / 10 papers shown
Title
Fine-tuning of explainable CNNs for skin lesion classification based on dermatologists' feedback towards increasing trust
Md Abdul Kadir
Fabrizio Nunnari
Daniel Sonntag
FAtt
16
1
0
03 Apr 2023
Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanations
Valerie Chen
Q. V. Liao
Jennifer Wortman Vaughan
Gagan Bansal
44
105
0
18 Jan 2023
A Human-ML Collaboration Framework for Improving Video Content Reviews
Meghana Deodhar
Xiao Ma
Yixin Cai
Alex Koes
Alex Beutel
Jilin Chen
29
3
0
18 Oct 2022
Mediators: Conversational Agents Explaining NLP Model Behavior
Nils Feldhus
A. Ravichandran
Sebastian Möller
43
16
0
13 Jun 2022
Perspectives on Incorporating Expert Feedback into Model Updates
Valerie Chen
Umang Bhatt
Hoda Heidari
Adrian Weller
Ameet Talwalkar
35
11
0
13 May 2022
Human-AI Collaboration via Conditional Delegation: A Case Study of Content Moderation
Vivian Lai
Samuel Carton
Rajat Bhatnagar
Vera Liao
Yunfeng Zhang
Chenhao Tan
29
130
0
25 Apr 2022
Towards a Science of Human-AI Decision Making: A Survey of Empirical Studies
Vivian Lai
Chacha Chen
Q. V. Liao
Alison Smith-Renner
Chenhao Tan
33
186
0
21 Dec 2021
Facilitating Knowledge Sharing from Domain Experts to Data Scientists for Building NLP Models
Soya Park
A. Wang
B. Kawas
Q. V. Liao
David Piorkowski
Marina Danilevsky
62
55
0
29 Jan 2021
Soliciting Human-in-the-Loop User Feedback for Interactive Machine Learning Reduces User Trust and Impressions of Model Accuracy
Donald R. Honeycutt
Mahsan Nourani
Eric D. Ragan
HAI
30
61
0
28 Aug 2020
Towards A Rigorous Science of Interpretable Machine Learning
Finale Doshi-Velez
Been Kim
XAI
FaML
257
3,696
0
28 Feb 2017
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