Mark Steyvers

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 37

Top Topics

Autonomous Driving

Nondeterministic Domains

Top Venues

Publications

Mark Steyvers, Heliodoro Tejeda Lemus, Aakriti Kumar, Catarina Belém, Sheer Karny, Xinyue Hu, Lukas Mayer, Padhraic Smyth
The Calibration Gap between Model and Human Confidence in Large Language Models. CoRR (2024)
Samuel Showalter, Alex J. Boyd, Padhraic Smyth, Mark Steyvers
Bayesian Online Learning for Consensus Prediction. AISTATS (2024)
Quentin F. Gronau, Mark Steyvers, Scott D. Brown
How do you know that you don't know? Cogn. Syst. Res. 86 (2024)
Catarina G. Belém, Markelle Kelly, Mark Steyvers, Sameer Singh, Padhraic Smyth
Perceptions of Linguistic Uncertainty by Language Models and Humans. CoRR (2024)
Sheer Karny, Lukas William Mayer, Jackie Ayoub, Miao Song, Haotian Su, Danyang Tian, Ehsan Moradi-Pari, Mark Steyvers
Learning with AI Assistance: A Path to Better Task Performance or Dependence? CI (2024)
Daniel M. Benjamin, Fred Morstatter, Ali E. Abbas, Andrés Abeliuk, Pavel Atanasov, Stephen Bennett, Andreas Beger, Saurabh Birari, David V. Budescu, Michele Catasta, Emilio Ferrara, Lucas Haravitch, Mark Himmelstein, K. S. M. Tozammel Hossain, Yuzhong Huang, Woojeong Jin, Regina Joseph, Jure Leskovec, Akira Matsui, Mehrnoosh Mirtaheri, Xiang Ren, Gleb Satyukov, Rajiv Sethi, Amandeep Singh, Rok Sosic, Mark Steyvers, Pedro A. Szekely, Michael D. Ward, Aram Galstyan
. AI Mag. 44 (1) (2023)
Aakriti Kumar, Kumar Akash, Shashank Mehrotra, Teruhisa Misu, Mark Steyvers
When Do Drivers Intervene In Autonomous Driving? HRI (Companion) (2023)
Abhilasha Ashok Kumar, Mark Steyvers
Help me help you: A computational model for goal inference and action planning. CogSci (2023)
Xinyi Wang, Wanrong Zhu, Michael Saxon, Mark Steyvers, William Yang Wang
Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context Learning. NeurIPS (2023)
Samuel Showalter, Alex Boyd, Padhraic Smyth, Mark Steyvers
Bayesian Online Learning for Consensus Prediction. CoRR (2023)
Heliodoro Tejeda Lemus, Aakriti Kumar, Mark Steyvers
How Displaying AI Confidence Affects Reliance and Hybrid Human-AI Performance. HHAI (2023)
Markelle Kelly, Aakriti Kumar, Padhraic Smyth, Mark Steyvers
Capturing Humans' Mental Models of AI: An Item Response Theory Approach. CoRR (2023)
Mark Steyvers
Human-AI collaboration (Conference Presentation). Medical Imaging: Image Perception, Observer Performance, and Technology Assessment (2023)
Markelle Kelly, Aakriti Kumar, Padhraic Smyth, Mark Steyvers
Capturing Humans' Mental Models of AI: An Item Response Theory Approach. FAccT (2023)
Heliodoro Tejeda Lemus, Aakriti Kumar, Mark Steyvers
An Empirical Investigation of Reliance on AI-Assistance in a Noisy-Image Classification Task. HHAI (2022)
Abhilasha Ashok Kumar, Mark Steyvers, David A. Balota
A Critical Review of Network-Based and Distributional Approaches to Semantic Memory Structure and Processes. Top. Cogn. Sci. 14 (1) (2022)
Aakriti Kumar, Trisha Patel, Aaron S. Benjamin, Mark Steyvers
Explaining Algorithm Aversion with Metacognitive Bandits. CogSci (2021)
Gavin Kerrigan, Padhraic Smyth, Mark Steyvers
Combining Human Predictions with Model Probabilities via Confusion Matrices and Calibration. NeurIPS (2021)
Gavin Kerrigan, Padhraic Smyth, Mark Steyvers
Combining Human Predictions with Model Probabilities via Confusion Matrices and Calibration. CoRR (2021)
Alexander H. Bower, Mark Steyvers
The Funny Thing About Algorithm Aversion: Investigating Bias Toward AI Humor. CogSci (2021)
Disi Ji, Robert L. Logan IV, Padhraic Smyth, Mark Steyvers
Active Bayesian Assessment of Black-Box Classifiers. AAAI (2021)
Abhilasha Ashok Kumar, Mark Steyvers, David A. Balota
Semantic Memory Search and Retrieval in a Novel Cooperative Word Game: A Comparison of Associative and Distributional Semantic Models. Cogn. Sci. 45 (10) (2021)
Disi Ji, Padhraic Smyth, Mark Steyvers
Can I Trust My Fairness Metric? Assessing Fairness with Unlabeled Data and Bayesian Inference. NeurIPS (2020)
Alexander Bower, Mark Steyvers
An Aha! Walks into a Bar: Joke Completion as a Form of Insight Problem Solving. CogSci (2020)
Disi Ji, Robert L. Logan IV, Padhraic Smyth, Mark Steyvers
Active Bayesian Assessment for Black-Box Classifiers. CoRR (2020)
Disi Ji, Padhraic Smyth, Mark Steyvers
Can I Trust My Fairness Metric? Assessing Fairness with Unlabeled Data and Bayesian Inference. CoRR (2020)
Garren Gaut, Brandon M. Turner, Zhong-Lin Lu, Xiangrui Li, William A. Cunningham, Mark Steyvers
Predicting Task and Subject Differences with Functional Connectivity and Blood-Oxygen-Level-Dependent Variability. Brain Connect. 9 (6) (2019)
Arsenii Moskvichev, Roman Tikhonov, Mark Steyvers
A Picture is Worth 7.17 Words: Learning Categories from Examples and Definitions. CogSci (2019)
Alexander Bower, Andrew Burton, Mark Steyvers, William H. Batchelder
An Insight into Language: Investigating Lexical and Morphological Effects in Compound Remote Associate Problem Solving. CogSci (2019)
Emily S. Sumner, Mark Steyvers, Barbara W. Sarnecka
It's not the treasure, it's the hunt: Children are more explorative on an explore/exploit task than adults. CogSci (2019)
Fred Morstatter, Aram Galstyan, Gleb Satyukov, Daniel Benjamin, Andrés Abeliuk, Mehrnoosh Mirtaheri, KSM Tozammel Hossain, Pedro A. Szekely, Emilio Ferrara, Akira Matsui, Mark Steyvers, Stephen Bennett, David V. Budescu, Mark Himmelstein, Michael D. Ward, Andreas Beger, Michele Catasta, Rok Sosic, Jure Leskovec, Pavel Atanasov, Regina Joseph, Rajiv Sethi, Ali E. Abbas
SAGE: A Hybrid Geopolitical Event Forecasting System. IJCAI (2019)
Abhilasha Ashok Kumar, David A. Balota, Mark Steyvers
Distant Concept Connectivity in Network-Based and Spatial Word Representations. CogSci (2019)
Nathan J. Evans, Mark Steyvers, Scott D. Brown
Modeling the Covariance Structure of Complex Datasets Using Cognitive Models: An Application to Individual Differences and the Heritability of Cognitive Ability. Cogn. Sci. 42 (6) (2018)
Brent Miller, Mark Steyvers
Leveraging Response Consistency within Individuals to Improve Group Accuracy for Rank-Ordering Problems. CogSci (2017)
Stephen Bennett, Aaron Benjamin, Mark Steyvers
A Bayesian model of knowledge and metacognitive control: Applications to opt-in tasks. CogSci (2017)
Garren Gaut, Mark Steyvers, Zac E. Imel, David C. Atkins, Padhraic Smyth
Content Coding of Psychotherapy Transcripts Using Labeled Topic Models. IEEE J. Biomed. Health Informatics 21 (2) (2017)
Brandon M. Turner, Christian A. Rodriguez, Anthony M. Norcia, Samuel M. McClure, Mark Steyvers
Why more is better: Simultaneous modeling of EEG, fMRI, and behavioral data. NeuroImage 128 (2016)
Michael D. Lee, Emily Liu, Mark Steyvers
The Roles of Knowledge and Memory in Generating Top-10 Lists. CogSci (2015)
Woojae Kim, Mark A. Pitt, Zhong-Lin Lu, Mark Steyvers, Jay I. Myung
A Hierarchical Adaptive Approach to Optimal Experimental Design. Neural Comput. 26 (11) (2014)
Woojae Kim, Mark A. Pitt, Zhong-Lin Lu, Mark Steyvers, Hairong Gu, Jay I. Myung
A Hierarchical Adaptive Approach to the Optimal Design of Experiments. CogSci (2014)
Brandon M. Turner, Mark Steyvers, Edgar C. Merkle, David V. Budescu, Thomas S. Wallsten
Forecast aggregation via recalibration. Mach. Learn. 95 (3) (2014)
Sean Tauber, Mark Steyvers
Inferring Subjective Prior Knowledge: An Integrative Bayesian Approach. CogSci (2013)
Qiang Liu, Alexander T. Ihler, Mark Steyvers
Scoring Workers in Crowdsourcing: How Many Control Questions are Enough? NIPS (2013)
Brandon M. Turner, Birte U. Forstmann, Eric-Jan Wagenmakers, Scott D. Brown, Per B. Sederberg, Mark Steyvers
A Bayesian framework for simultaneously modeling neural and behavioral data. NeuroImage 72 (2013)
Edgar C. Merkle, Mark Steyvers
Choosing a Strictly Proper Scoring Rule. Decis. Anal. 10 (4) (2013)
Michael D. Lee, Mark Steyvers, Mindy de Young, Brent Miller
Inferring Expertise in Knowledge and Prediction Ranking Tasks. Top. Cogn. Sci. 4 (1) (2012)
Sheng Kung Michael Yi, Mark Steyvers, Michael D. Lee, Matthew J. Dry
The Wisdom of the Crowd in Combinatorial Problems. Cogn. Sci. 36 (3) (2012)
Nicole Beckage, Mark Steyvers, Carter T. Butts
Route choice in individuals - semantic network navigation. CogSci (2012)
Timothy N. Rubin, America Chambers, Padhraic Smyth, Mark Steyvers
Statistical topic models for multi-label document classification. Mach. Learn. 88 (1-2) (2012)
Dirk B. Warnaar, Edgar C. Merkle, Mark Steyvers, Thomas S. Wallsten, Eric R. Stone, David V. Budescu, J. Frank Yates, Winston R. Sieck, Hal R. Arkes, Chris F. Argenta, Youngwon Shin, Jennifer N. Carter
The Aggregative Contingent Estimation System: Selecting, Rewarding, and Training Experts in a Wisdom of Crowds Approach to Forecasting. AAAI Spring Symposium: Wisdom of the Crowd (2012)
Michal Rosen-Zvi, Thomas L. Griffiths, Mark Steyvers, Padhraic Smyth
The Author-Topic Model for Authors and Documents CoRR (2012)
Lisa Pearl, Mark Steyvers
Detecting authorship deception: a supervised machine learning approach using author writeprints. Lit. Linguistic Comput. 27 (2) (2012)
Guy Hawkins, Scott D. Brown, Mark Steyvers, Eric-Jan Wagenmakers
Context Effects in Multi-Alternative Decision Making: Empirical Data and a Bayesian Model. Cogn. Sci. 36 (3) (2012)
Brent Miller, Mark Steyvers
The Wisdom of Crowds with Communication. CogSci (2011)
Sean Tauber, Mark Steyvers
Using Inverse Planning and Theory of Mind for Social Goal Inference. CogSci (2011)
Timothy N. Rubin, America Chambers, Padhraic Smyth, Mark Steyvers
Statistical Topic Models for Multi-Label Document Classification CoRR (2011)
Timothy N. Rubin, Matthew D. Zeigenfuse, Mark Steyvers
A Model of Concept Generalization and Feature Representation in Hierarchies. CogSci (2011)
Michael D. Lee, Shunan Zhang, Miles Munro, Mark Steyvers
Psychological models of human and optimal performance in bandit problems. Cogn. Syst. Res. 12 (2) (2011)
Michael D. Lee, Mark Steyvers, Mindy de Young, Brent Miller
A Model-Based Approach to Measuring Expertise in Ranking Tasks. CogSci (2011)
Edgar C. Merkle, Mark Steyvers
A Psychological Model for Aggregating Judgments of Magnitude. SBP (2011)
Mark Steyvers, Padhraic Smyth, Chaitanya Chemudugunta
Combining Background Knowledge and Learned Topics. Top. Cogn. Sci. 3 (1) (2011)
America Chambers, Padhraic Smyth, Mark Steyvers
Learning concept graphs from text with stick-breaking priors. NIPS (2010)
Michal Rosen-Zvi, Chaitanya Chemudugunta, Thomas L. Griffiths, Padhraic Smyth, Mark Steyvers
Learning author-topic models from text corpora. ACM Trans. Inf. Syst. 28 (1) (2010)
Pernille Hemmer, Mark Steyvers
A Bayesian Account of Reconstructive Memory. Top. Cogn. Sci. 1 (1) (2009)
Sheng Kung Michael Yi, Mark Steyvers, Michael D. Lee
Modeling Human Performance in Restless Bandits with Particle Filters. J. Probl. Solving 2 (2) (2009)
Mark Steyvers, Michael D. Lee, Brent Miller, Pernille Hemmer
The Wisdom of Crowds in the Recollection of Order Information. NIPS (2009)
Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyvers
Combining concept hierarchies and statistical topic models. CIKM (2008)
Chaitanya Chemudugunta, America Holloway, Padhraic Smyth, Mark Steyvers
Modeling Documents by Combining Semantic Concepts with Unsupervised Statistical Learning. ISWC (2008)
Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyvers
Text Modeling using Unsupervised Topic Models and Concept Hierarchies CoRR (2008)
Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyvers
Modeling General and Specific Aspects of Documents with a Probabilistic Topic Model. NIPS (2006)
David Newman, Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyvers
Analyzing Entities and Topics in News Articles Using Statistical Topic Models. ISI (2006)
Mark Steyvers, Joshua B. Tenenbaum
The Large-Scale Structure of Semantic Networks: Statistical Analyses and a Model of Semantic Growth. Cogn. Sci. 29 (1) (2005)
Mark Steyvers, Scott D. Brown
Prediction and Change Detection. NIPS (2005)
Michal Rosen-Zvi, Thomas L. Griffiths, Mark Steyvers, Padhraic Smyth
The Author-Topic Model for Authors and Documents. UAI (2004)
Thomas L. Griffiths, Mark Steyvers, David M. Blei, Joshua B. Tenenbaum
Integrating Topics and Syntax. NIPS (2004)
Mark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, Thomas L. Griffiths
Probabilistic author-topic models for information discovery. KDD (2004)
Mark Steyvers, Joshua B. Tenenbaum, Eric-Jan Wagenmakers, Ben Blum
Inferring causal networks from observations and interventions. Cogn. Sci. 27 (3) (2003)
Thomas L. Griffiths, Mark Steyvers
Prediction and Semantic Association. NIPS (2002)