Visualizing Scissors Congruence. - Satyan L. Devadoss; Ziv Epstein; Dmitriy Smirnov 001 (SoCG, 2016)

The Good, the Bad, and the Unflinchingly Selfish: Cooperative Decision-Making can be Predicted with high Accuracy when using only Three Behavioral Types. - Ziv Epstein; Alexander Peysakhovich; David G. Rand (EC, 2016)

Using clinical data to predict high-cost performance coding issues associated with pressure ulcers: a multilevel cohort model. - William V. Padula; Robert D. Gibbons; Peter J. Pronovost; Donald Hedeker; Manish K. Mishra; Mary B. Makic; John F. P. Bridges; Heidi L. Wald; Robert Valuck; Adam J. Ginensky; Anthony Ursitti; Laura Ruth Venable; et al. (J. Am. Medical Informatics Assoc., 2017)

TuringBox: An Experimental Platform for the Evaluation of AI Systems. - Ziv Epstein; Blakeley H. Payne; Judy Hanwen Shen; Casey Jisoo Hong; Bjarke Felbo; Abhimanyu Dubey; Matthew Groh; Nick Obradovich; Manuel Cebrián; Iyad Rahwan (IJCAI, 2018)

Closing the AI Knowledge Gap. - Ziv Epstein; Blakeley H. Payne; Judy Hanwen Shen; Abhimanyu Dubey; Bjarke Felbo; Matthew Groh; Nick Obradovich; Manuel Cebrián; Iyad Rahwan (CoRR, 2018)

Towards a new social laboratory: An experimental study of search through community participation at Burning Man. - Ziv Epstein; Micah Epstein; Christian Almenar; Matthew Groh; Niccolo Pescetelli; Esteban Moro; Nick Obradovich; Manuel Cebrián; Iyad Rahwan (CoRR, 2019)

The Good, the Bad, and the Unflinchingly Selfish: Pro-sociality can be Well Predicted Using Payoffs and Three Behavioral Types. - Ziv Epstein; Alexander Peysakhovich; David G. Rand (ACM Trans. Economics and Comput., 2019)

Will the Crowd Game the Algorithm?: Using Layperson Judgments to Combat Misinformation on Social Media by Downranking Distrusted Sources. - Ziv Epstein; Gordon Pennycook; David G. Rand (CHI, 2020)

Interpolating GANs to Scaffold Autotelic Creativity. - Ziv Epstein; Océane Boulais; Skylar Gordon; Matthew Groh (CoRR, 2020)

Human detection of machine-manipulated media. - Matthew Groh; Ziv Epstein; Nick Obradovich; Manuel Cebrián; Iyad Rahwan (Commun. ACM, 2021)

Comparing Human and Machine Deepfake Detection with Affective and Holistic Processing. - Matthew Groh; Ziv Epstein; Chaz Firestone; Rosalind W. Picard (CoRR, 2021)

Social Influence Leads to the Formation of Diverse Local Trends. - Ziv Epstein; Matthew Groh; Abhimanyu Dubey; Alex Pentland (Proc. ACM Hum. Comput. Interact., 2021)

When happy accidents spark creativity: Bringing collaborative speculation to life with generative AI. - Ziv Epstein; Hope Schroeder; Dava J. Newman (ICCC, 2022)

Co-creation and ownership for AI radio. - Skylar Gordon; Robert Mahari; Manaswi Mishra; Ziv Epstein (ICCC, 2022)

Do Explanations Increase the Effectiveness of AI-Crowd Generated Fake News Warnings? - Ziv Epstein; Nicolò Foppiani; Sophie Hilgard; Sanjana Sharma; Elena L. Glassman; David G. Rand (ICWSM, 2022)

Yourfeed: Towards open science and interoperable systems for social media. - Ziv Epstein; Hause Lin (CoRR, 2022)

How many others have shared this? Experimentally investigating the effects of social cues on engagement, misinformation, and unpredictability on social media. - Ziv Epstein; Hause Lin; Gordon Pennycook; David G. Rand (CoRR, 2022)

Quantifying attention via dwell time and engagement in a social media browsing environment. - Ziv Epstein; Hause Lin; Gordon Pennycook; David G. Rand (CoRR, 2022)

Deceptive AI Systems That Give Explanations Are Just as Convincing as Honest AI Systems in Human-Machine Decision Making. - Valdemar Danry; Pat Pataranutaporn; Ziv Epstein; Matthew Groh; Pattie Maes (CoRR, 2022)

Trash to Treasure: Using text-to-image models to inform the design of physical artefacts. - Amy Smith; Hope Schroeder; Ziv Epstein; Michael Cook 001; Simon Colton; Andrew Lippman (CoRR, 2023)

Art and the science of generative AI: A deeper dive. - Ziv Epstein; Aaron Hertzmann; Laura Mariah Herman; Robert Mahari; Morgan R. Frank; Matthew Groh; Hope Schroeder; Amy Smith; Memo Akten; Jessica Fjeld; Hany Farid; Neil Leach; et al. (CoRR, 2023)

LLMs as Research Tools: Applications and Evaluations in HCI Data Work. - Marianne Aubin Le Quéré; Hope Schroeder; Casey Randazzo; Jie Gao; Ziv Epstein; Simon Tangi Perrault; David Mimno; Louise Barkhuus; Hanlin Li (CHI Extended Abstracts, 2024)

Deceptive AI systems that give explanations are more convincing than honest AI systems and can amplify belief in misinformation. - Valdemar Danry; Pat Pataranutaporn; Matthew Groh; Ziv Epstein; Pattie Maes (CoRR, 2024)

Deceptive Explanations by Large Language Models Lead People to Change their Beliefs About Misinformation More Often than Honest Explanations. - Valdemar Danry; Pat Pataranutaporn; Matthew Groh; Ziv Epstein (CHI, 2025)