Joyce Zhou

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All published works

Action	Title	Year	Authors
+ PDF Chat	End-to-end Training for Recommendation with Language-based User Profiles	2024	Zhaolin Gao Joyce Zhou Yijia Dai Thorsten Joachims
+ PDF Chat	Algorithms for College Admissions Decision Support: Impacts of Policy Change and Inherent Variability	2024	Jin-Sook Lee Emma Harvey Joyce Zhou Nikhil Garg Thorsten Joachims René F. Kizilcec
+ PDF Chat	Language-Based User Profiles for Recommendation	2024	Joyce Zhou Yijia Dai Thorsten Joachims
+ PDF Chat	Augmenting Holistic Review in University Admission using Natural Language Processing for Essays and Recommendation Letters	2023	Jin-Sook Lee Bradon Thymes Joyce Zhou Thorsten Joachims René F. Kizilcec
+	Augmenting Holistic Review in University Admission using Natural Language Processing for Essays and Recommendation Letters	2023	Jin-Sook Lee Bradon Thymes Joyce Zhou Thorsten Joachims René F. Kizilcec
+	GPT as a Baseline for Recommendation Explanation Texts	2023	Joyce Zhou Thorsten Joachims
+ PDF Chat	Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance	2021	Gagan Bansal Tongshuang Wu Joyce Zhou Raymond Fok Besmira Nushi Ece Kamar Marco Túlio Ribeiro Daniel S. Weld
+	Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance	2020	Gagan Bansal Tongshuang Wu Joyce Zhou Raymond Fok Besmira Nushi Ece Kamar Marco Túlio Ribeiro Daniel S. Weld

Common Coauthors

Coauthor	Papers Together
Thorsten Joachims	6
René F. Kizilcec	3
Jin-Sook Lee	3
Marco Túlio Ribeiro	2
Ece Kamar	2
Bradon Thymes	2
Gagan Bansal	2
Raymond Fok	2
Tongshuang Wu	2
Daniel S. Weld	2
Yijia Dai	2
Besmira Nushi	2
Zhaolin Gao	1
Nikhil Garg	1
Emma Harvey	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	'It's Reducing a Human Being to a Percentage': Perceptions of Justice in Algorithmic Decisions	2018	Reuben Binns Max Van Kleek Michael Veale Ulrik Lyngs Jun Zhao Nigel Shadbolt	2
+	Keeping Community in the Loop: Understanding Wikipedia Stakeholder Values for Machine Learning-Based Systems	2020	C. Estelle Smith Bowen Yu Anjali Srivastava Aaron Halfaker Loren Terveen Haiyi Zhu	2
+	Explainable machine learning in deployment	2020	Umang Bhatt Alice Xiang Shubham Sharma Adrian Weller Ankur Taly Yunhan Jia Joydeep Ghosh Ruchir Puri José M. F. Moura Peter Eckersley	2
+	Optimizing AI for Teamwork.	2020	Gagan Bansal Besmira Nushi Ece Kamar Eric Horvitz Daniel S. Weld	2
+ PDF Chat	"Why is 'Chicago' deceptive?" Towards Building Model-Driven Tutorials for Humans	2020	Vivian Lai Han Liu Chenhao Tan	2
+	Learning to Complement Humans	2020	Bryan Wilder Eric Horvitz Ece Kamar	2
+	Evaluating Explainable AI: Which Algorithmic Explanations Help Users Predict Model Behavior?	2020	Peter Hase Mohit Bansal	2
+ PDF Chat	Ups and Downs: Modeling the Visual Evolution of Fashion Trends with One-Class Collaborative Filtering	2016	Ruining He Julian McAuley	2
+	Manipulating and Measuring Model Interpretability	2018	Forough Poursabzi-Sangdeh Daniel G. Goldstein Jake M. Hofman Jennifer Wortman Vaughan Hanna Wallach	2
+	Why Interpretability in Machine Learning? An Answer Using Distributed Detection and Data Fusion Theory.	2018	Kush R. Varshney Prashant Khanduri Pranay Sharma Shan Zhang Pramod K. Varshney	2
+ PDF Chat	Proxy tasks and subjective measures can be misleading in evaluating explainable AI systems	2020	Zana Buçinca Phoebe Lin Krzysztof Z. Gajos Elena L. Glassman	2
+ PDF Chat	Effect of confidence and explanation on accuracy and trust calibration in AI-assisted decision making	2020	Yunfeng Zhang Q. Vera Liao Rachel Bellamy	2
+ PDF Chat	The Mythos of Model Interpretability	2018	Zachary C. Lipton	2
+ PDF Chat	Interpreting Recurrent and Attention-Based Neural Models: a Case Study on Natural Language Inference	2018	Reza Ghaeini Xiaoli Z. Fern Prasad Tadepalli	2
+	Investigating Human + Machine Complementarity for Recidivism Predictions	2018	Sarah Tan Julius Adebayo Kori Inkpen Ece Kamar	2
+ PDF Chat	Do explanations make VQA models more predictable to a human?	2018	Arjun Chandrasekaran Viraj Prabhu Deshraj Jain Prithvijit Chattopadhyay Devi Parikh	2
+ PDF Chat	On Human Predictions with Explanations and Predictions of Machine Learning Models	2019	Vivian Lai Chenhao Tan	2
+ PDF Chat	Learning Attitudes and Attributes from Multi-aspect Reviews	2012	Julian McAuley Jure Leskovec Dan Jurafsky	2
+	Quantifying Interpretability and Trust in Machine Learning Systems	2019	Philipp Schmidt Felix Bießmann	2
+ PDF Chat	Incentivizing High Quality Crowdwork	2015	Chien-Ju Ho Aleksandrs Slivkins Siddharth Suri Jennifer Wortman Vaughan	2
+	The Isotonic Regression Problem and its Dual	1972	Richard E. Barlow H. D. Brunk	2
+	A Human-Grounded Evaluation of SHAP for Alert Processing.	2019	Hilde Weerts Werner van Ipenburg Mykola Pechenizkiy	2
+ PDF Chat	The mythos of model interpretability	2018	Zachary C. Lipton	2
+	Interpretable and Explorable Approximations of Black Box Models	2017	Himabindu Lakkaraju Ece Kamar Rich Caruana Jure Leskovec	2
+	Natural Language Generation enhances human decision-making with uncertain information	2016	Dimitra Gkatzia Oliver Lemon Verena Rieser	2
+ PDF Chat	Teaching Categories to Human Learners with Visual Explanations	2018	Oisin Mac Aodha Shihan Su Yuxin Chen Pietro Perona Yisong Yue	2
+ PDF Chat	The challenge of crafting intelligible intelligence	2019	Daniel S. Weld Gagan Bansal	2
+	RoBERTa: A Robustly Optimized BERT Pretraining Approach	2019	Yinhan Liu Myle Ott Naman Goyal Jingfei Du Mandar Joshi Danqi Chen Omer Levy Mike Lewis Luke Zettlemoyer Veselin Stoyanov	2
+	How do Humans Understand Explanations from Machine Learning Systems? An Evaluation of the Human-Interpretability of Explanation.	2018	Menaka Narayanan Emily Chen Jeffrey He Been Kim Sam Gershman Finale Doshi‐Velez	2
+ PDF Chat	Ups and Downs	2016	Ruining He Julian McAuley	1
+	Rationalizing Neural Predictions	2016	Tao Leí Regina Barzilay Tommi Jaakkola	1
+	A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks	2016	Dan Hendrycks Kevin Gimpel	1
+ PDF Chat	Identifying Unknown Unknowns in the Open World: Representations and Policies for Guided Exploration	2017	Himabindu Lakkaraju Ece Kamar Rich Caruana Eric Horvitz	1
+	Understanding Black-box Predictions via Influence Functions	2017	Pang Wei Koh Percy Liang	1
+	Proceedings of the 25th international conference on Machine learning	2008	William W. Cohen Andrew McCallum Sam T. Roweis	1
+	Axiomatic Attribution for Deep Networks	2017	Mukund Sundararajan Ankur Taly Qiqi Yan	1
+	Equality of Opportunity in Supervised Learning	2016	Moritz Hardt Eric Price Nathan Srebro	1
+	Explanation in artificial intelligence: Insights from the social sciences	2018	Tim Miller	1
+	AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models	2019	Eric Wallace Jens Tuyls Junlin Wang Sanjay Subramanian Matt Gardner Sameer Singh	1
+	ReClor: A Reading Comprehension Dataset Requiring Logical Reasoning	2020	Weihao Yu Zihang Jiang Yanfei Dong Jiashi Feng	1
+ PDF Chat	Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Data	2019	Jackson A. Killian Bryan Wilder Amit Sharma Vinod Choudhary Bistra Dilkina Milind Tambe	1
+ PDF Chat	Model Cards for Model Reporting	2019	Margaret Mitchell Simone Wu Andrew Zaldivar Parker Barnes Lucy Vasserman Ben Hutchinson Elena Spitzer Inioluwa Deborah Raji Timnit Gebru	1
+ PDF Chat	'It's Reducing a Human Being to a Percentage'	2018	Reuben Binns Max Van Kleek Michael Veale Ulrik Lyngs Jun Zhao Nigel Shadbolt	1
+	Proceedings of the 24th international conference on Machine learning	2007	John Langford Joëlle Pineau	1