Jake M. Hofman

50 papers A* 15A 4Journal 23Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Agentic Markets: Equilibrium Effects of Improving Consumer Search. CoRR Brendan Lucier, Nicole Immorlica, Markus Mobius, Aleksandrs Slivkins, Daniel G. Goldstein, Jake M. Hofman, Sonia Jaffe, David M. Rothschild
2026	—	`conf`	Effects of Generative AI Errors on User Reliance Across Task Difficulty. CHI Extended Abstracts Jacy Reese Anthis, Hannah Cha, Solon Barocas, Alexandra Chouldechova, Jake M. Hofman
2026	J	`jnl`	Effects of LLM use and note-taking on reading comprehension and memory: A randomised experiment in secondary schools. Comput. Educ. Pia Kreijkes, Viktor Kewenig, Martina Kuvalja, Mina Lee, Jake M. Hofman, Sylvia Vitello, Abigail Sellen, Sean Rintel, Daniel G. Goldstein, David M. Rothschild, Lev Tankelevitch, Tim Oates
2026	J	`jnl`	The Agentic Economy. Commun. ACM David M. Rothschild, Markus Mobius, Jake M. Hofman, Eleanor Dillon, Daniel G. Goldstein, Nicole Immorlica, Sonia Jaffe, Brendan Lucier, Aleksandrs Slivkins, Matthew Vogel
2025	J	`jnl`	Bringing Everyone to the Table: An Experimental Study of LLM-Facilitated Group Decision Making. CoRR Mohammed Alsobay, David M. Rothschild, Jake M. Hofman, Daniel G. Goldstein
2025	—	`conf`	ChatBench: From Static Benchmarks to Human-AI Evaluation. ACL (1) Serina Chang, Ashton Anderson, Jake M. Hofman
2025	J	`jnl`	ChatBench: From Static Benchmarks to Human-AI Evaluation. CoRR Serina Chang, Ashton Anderson, Jake M. Hofman
2025	A*	`conf`	Effects of LLM-based Search on Decision Making: Speed, Accuracy, and Overreliance. CHI Sofia Eleni Spatharioti, David M. Rothschild, Daniel G. Goldstein, Jake M. Hofman
2025	J	`jnl`	Magentic Marketplace: An Open-Source Environment for Studying Agentic Markets. CoRR Gagan Bansal, Wenyue Hua, Zezhou Huang, Adam Fourney, Amanda Swearngin, Will Epperson, Tyler Payne, Jake M. Hofman, Brendan Lucier, Chinmay Singh, Markus Mobius, Akshay Nambi, Archana Yadav, Kevin Gao, David M. Rothschild, Aleksandrs Slivkins, Daniel G. Goldstein, Hussein Mozannar, Nicole Immorlica, Maya Murad, Matthew Vogel, Subbarao Kambhampati, Eric Horvitz, Saleema Amershi
2025	—	`conf`	Math Education With Large Language Models: Peril or Promise? AIED (4) Harsh Kumar, David M. Rothschild, Daniel G. Goldstein, Jake M. Hofman
2025	J	`jnl`	The Agentic Economy. CoRR David M. Rothschild, Markus Mobius, Jake M. Hofman, Eleanor Wiske Dillon, Daniel G. Goldstein, Nicole Immorlica, Sonia Jaffe, Brendan Lucier, Aleksandrs Slivkins, Matthew Vogel
2024	A*	`conf`	Using Open Data to Automatically Generate Localized Analogies. CHI Sofia Eleni Spatharioti, Daniel G. Goldstein, Jake M. Hofman
2023	J	`jnl`	Comparing Traditional and LLM-based Search for Consumer Choice: A Randomized Experiment. CoRR Sofia Eleni Spatharioti, David M. Rothschild, Daniel G. Goldstein, Jake M. Hofman
2023	J	`jnl`	Comparing scalable strategies for generating numerical perspectives. CoRR Hancheng Cao, Sofia Eleni Spatharioti, Daniel G. Goldstein, Jake M. Hofman
2023	—	`conf`	Multi-Target Multiplicity: Flexibility and Fairness in Target Specification under Resource Constraints. FAccT Jamelle Watson-Daniels, Solon Barocas, Jake M. Hofman, Alexandra Chouldechova
2023	J	`jnl`	Multi-Target Multiplicity: Flexibility and Fairness in Target Specification under Resource Constraints. CoRR Jamelle Watson-Daniels, Solon Barocas, Jake M. Hofman, Alexandra Chouldechova
2023	J	`jnl`	Pre-registration for Predictive Modeling. CoRR Jake M. Hofman, Angelos Chatzimparmpas, Amit Sharma, Duncan J. Watts, Jessica Hullman
2023	J	`jnl`	REFORMS: Reporting Standards for Machine Learning Based Science. CoRR Sayash Kapoor, Emily Cantrell, Kenny Peng, Thanh Hien Pham, Christopher A. Bail, Odd Erik Gundersen, Jake M. Hofman, Jessica Hullman, Michael A. Lones, Momin M. Malik, Priyanka Nanayakkara, Russell A. Poldrack, Inioluwa Deborah Raji, Michael Roberts, Matthew J. Salganik, Marta Serra-Garcia, Brandon M. Stewart, Gilles Vandewiele, Arvind Narayanan
2022	J	`jnl`	How Good is Good Enough? Quantifying the Impact of Benefits, Accuracy, and Privacy on Willingness to Adopt COVID-19 Decision Aids. DTRAP Gabriel Kaptchuk, Daniel G. Goldstein, Eszter Hargittai, Jake M. Hofman, Elissa M. Redmiles
2022	A*	`conf`	Investigating Perceptual Biases in Icon Arrays. CHI Cindy Xiong, Ali Sarvghad, Daniel G. Goldstein, Jake M. Hofman, Çagatay Demiralp
2022	A*	`conf`	Putting scientific results in perspective: Improving the communication of standardized effect sizes. CHI Yea-Seul Kim, Jake M. Hofman, Daniel G. Goldstein
2022	A*	`conf`	Round Numbers Can Sharpen Cognition. CHI Huy Anh Nguyen, Jake M. Hofman, Daniel G. Goldstein
2021	A*	`conf`	Datamations: Animated Explanations of Data Analysis Pipelines. CHI Xiaoying Pu, Sean Kross, Jake M. Hofman, Daniel G. Goldstein
2021	A*	`conf`	Manipulating and Measuring Model Interpretability. CHI Forough Poursabzi-Sangdeh, Daniel G. Goldstein, Jake M. Hofman, Jennifer Wortman Vaughan, Hanna M. Wallach
2020	—	`conf`	Expanding the Scope of Reproducibility Research Through Data Analysis Replications. WWW (Companion Volume) Jake M. Hofman, Daniel G. Goldstein, Siddhartha Sen, Forough Poursabzi-Sangdeh
2020	A*	`conf`	How Visualizing Inferential Uncertainty Can Mislead Readers About Treatment Effects in Scientific Results. CHI Jake M. Hofman, Daniel G. Goldstein, Jessica Hullman
2020	J	`jnl`	How good is good enough for COVID19 apps? The influence of benefits, accuracy, and privacy on willingness to adopt. CoRR Gabriel Kaptchuk, Daniel G. Goldstein, Eszter Hargittai, Jake M. Hofman, Elissa M. Redmiles
2018	J	`jnl`	Manipulating and Measuring Model Interpretability. CoRR Forough Poursabzi-Sangdeh, Daniel G. Goldstein, Jake M. Hofman, Jennifer Wortman Vaughan, Hanna M. Wallach
2018	A*	`conf`	To Put That in Perspective: Generating Analogies that Make Numbers Easier to Understand. CHI Christopher Riederer, Jake M. Hofman, Daniel G. Goldstein
2017	—	`conf`	What's Happening and What Happened: Searching the Social Web. WebSci Omar Alonso, Vasileios Kandylas, Serge-Eric Tremblay, Jake M. Hofman, Siddhartha Sen
2016	A*	`conf`	Exploring Limits to Prediction in Complex Social Systems. WWW Travis Martin, Jake M. Hofman, Amit Sharma, Ashton Anderson, Duncan J. Watts
2016	J	`jnl`	Exploring limits to prediction in complex social systems. CoRR Travis Martin, Jake M. Hofman, Amit Sharma, Ashton Anderson, Duncan J. Watts
2016	A*	`conf`	Improving Comprehension of Numbers in the News. CHI Pablo Javier Barrio, Daniel G. Goldstein, Jake M. Hofman
2016	J	`jnl`	Split-door criterion for causal identification: Automatic search for natural experiments. CoRR Amit Sharma, Jake M. Hofman, Duncan J. Watts
2016	J	`jnl`	The Structural Virality of Online Diffusion. Manag. Sci. Sharad Goel, Ashton Anderson, Jake M. Hofman, Duncan J. Watts
2015	A*	`conf`	Estimating the Causal Impact of Recommendation Systems from Observational Data. EC Amit Sharma, Jake M. Hofman, Duncan J. Watts
2015	J	`jnl`	Estimating the Causal Impact of Recommendation Systems from Observational Data. CoRR Amit Sharma, Jake M. Hofman, Duncan J. Watts
2015	A	`conf`	Scalable Recommendation with Hierarchical Poisson Factorization. UAI Prem Gopalan, Jake M. Hofman, David M. Blei
2014	—	`conf`	A large-scale exploration of group viewing patterns. TVX Allison June-Barlow Chaney, Mike Gartrell, Jake M. Hofman, John Guiver, Noam Koenigstein, Pushmeet Kohli, Ulrich Paquet
2013	J	`jnl`	Scalable Recommendation with Poisson Factorization. CoRR Prem Gopalan, Jake M. Hofman, David M. Blei
2013	A	`conf`	Sharding social networks. WSDM Quang Duong, Sharad Goel, Jake M. Hofman, Sergei Vassilvitskii
2012	A	`conf`	Who Does What on the Web: A Large-Scale Study of Browsing Behavior. ICWSM Sharad Goel, Jake M. Hofman, M. Irmak Sirer
2011	A	`conf`	Everyone's an influencer: quantifying influence on twitter. WSDM Eytan Bakshy, Jake M. Hofman, Winter A. Mason, Duncan J. Watts
2011	A*	`conf`	Who says what to whom on twitter. WWW Shaomei Wu, Jake M. Hofman, Winter A. Mason, Duncan J. Watts
2010	J	`jnl`	Graphical models for inferring single molecule dynamics. BMC Bioinform. Jonathan E. Bronson, Jake M. Hofman, Jingyi Fei, Ruben L. Gonzalez, Chris H. Wiggins
2010	A*	`conf`	Inferring relevant social networks from interpersonal communication. WWW Munmun De Choudhury, Winter A. Mason, Jake M. Hofman, Duncan J. Watts
2010	J	`jnl`	Predicting consumer behavior with Web search. Proc. Natl. Acad. Sci. USA Sharad Goel, Jake M. Hofman, Sébastien Lahaie, David M. Pennock, Duncan J. Watts
2009	J	`jnl`	Characterizing Individual Communication Patterns CoRR R. Dean Malmgren, Jake M. Hofman, Luís A. Nunes Amaral, Duncan J. Watts
2009	A*	`conf`	Characterizing individual communication patterns. KDD R. Dean Malmgren, Jake M. Hofman, Luís A. Nunes Amaral, Duncan J. Watts
2008	—	`conf`	Inferring the structure and scale of modular networks. MLG@ICML Jake M. Hofman, Chris H. Wiggins