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2020 – today
- 2024
[j24]Quentin F. Gronau
, Mark Steyvers, Scott D. Brown:
How do you know that you don't know? Cogn. Syst. Res. 86: 101232 (2024)- [c45]Samuel Showalter, Alex J. Boyd, Padhraic Smyth, Mark Steyvers:
Bayesian Online Learning for Consensus Prediction. AISTATS 2024: 2539-2547 - [c44]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 - [c43]Catarina G. Belém, Markelle Kelly, Mark Steyvers, Sameer Singh, Padhraic Smyth:
Perceptions of Linguistic Uncertainty by Language Models and Humans. EMNLP 2024: 8467-8502 - [i10]Mark Steyvers, Heliodoro Tejeda Lemus, Aakriti Kumar, Catarina G. Belém, Sheer Karny, Xinyue Hu, Lukas William Mayer, Padhraic Smyth:
The Calibration Gap between Model and Human Confidence in Large Language Models. CoRR abs/2401.13835 (2024) - [i9]Catarina G. Belém, Markelle Kelly, Mark Steyvers, Sameer Singh, Padhraic Smyth:
Perceptions of Linguistic Uncertainty by Language Models and Humans. CoRR abs/2407.15814 (2024) - 2023
- [j23]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:
Hybrid forecasting of geopolitical events†. AI Mag. 44(1): 112-128 (2023) - [c42]Abhilasha Ashok Kumar, Mark Steyvers:
Help me help you: A computational model for goal inference and action planning. CogSci 2023 - [c41]Markelle Kelly, Aakriti Kumar, Padhraic Smyth, Mark Steyvers:
Capturing Humans' Mental Models of AI: An Item Response Theory Approach. FAccT 2023: 1723-1734 - [c40]Heliodoro Tejeda Lemus, Aakriti Kumar, Mark Steyvers:
How Displaying AI Confidence Affects Reliance and Hybrid Human-AI Performance. HHAI 2023: 234-242 - [c39]Aakriti Kumar, Kumar Akash, Shashank Mehrotra, Teruhisa Misu, Mark Steyvers:
When Do Drivers Intervene In Autonomous Driving? HRI (Companion) 2023: 301-305 - [c38]Mark Steyvers:
Human-AI collaboration (Conference Presentation). Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2023 - [c37]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 - [i8]Markelle Kelly, Aakriti Kumar, Padhraic Smyth, Mark Steyvers:
Capturing Humans' Mental Models of AI: An Item Response Theory Approach. CoRR abs/2305.09064 (2023) - [i7]Samuel Showalter, Alex Boyd, Padhraic Smyth, Mark Steyvers:
Bayesian Online Learning for Consensus Prediction. CoRR abs/2312.07679 (2023) - 2022
- [j22]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): 54-77 (2022) - [c36]Heliodoro Tejeda Lemus, Aakriti Kumar, Mark Steyvers:
An Empirical Investigation of Reliance on AI-Assistance in a Noisy-Image Classification Task. HHAI 2022: 225-237 - 2021
- [j21]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) - [c35]Disi Ji, Robert L. Logan IV, Padhraic Smyth, Mark Steyvers:
Active Bayesian Assessment of Black-Box Classifiers. AAAI 2021: 7935-7944 - [c34]Alexander H. Bower, Mark Steyvers:
The Funny Thing About Algorithm Aversion: Investigating Bias Toward AI Humor. CogSci 2021 - [c33]Aakriti Kumar, Trisha Patel, Aaron S. Benjamin, Mark Steyvers:
Explaining Algorithm Aversion with Metacognitive Bandits. CogSci 2021 - [c32]Gavin Kerrigan, Padhraic Smyth, Mark Steyvers:
Combining Human Predictions with Model Probabilities via Confusion Matrices and Calibration. NeurIPS 2021: 4421-4434 - [i6]Gavin Kerrigan, Padhraic Smyth, Mark Steyvers:
Combining Human Predictions with Model Probabilities via Confusion Matrices and Calibration. CoRR abs/2109.14591 (2021) - 2020
- [c31]Alexander H. Bower, Mark Steyvers:
An Aha! Walks into a Bar: Joke Completion as a Form of Insight Problem Solving. CogSci 2020 - [c30]Disi Ji, Padhraic Smyth, Mark Steyvers:
Can I Trust My Fairness Metric? Assessing Fairness with Unlabeled Data and Bayesian Inference. NeurIPS 2020 - [i5]Disi Ji, Robert L. Logan IV, Padhraic Smyth, Mark Steyvers:
Active Bayesian Assessment for Black-Box Classifiers. CoRR abs/2002.06532 (2020) - [i4]Disi Ji, Padhraic Smyth, Mark Steyvers:
Can I Trust My Fairness Metric? Assessing Fairness with Unlabeled Data and Bayesian Inference. CoRR abs/2010.09851 (2020)
2010 – 2019
- 2019
- [j20]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): 451-463 (2019) - [c29]Alexander H. 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: 166-173 - [c28]Abhilasha Ashok Kumar, David A. Balota, Mark Steyvers:
Distant Concept Connectivity in Network-Based and Spatial Word Representations. CogSci 2019: 1348-1354 - [c27]Arsenii Moskvichev, Roman Tikhonov, Mark Steyvers:
A Picture is Worth 7.17 Words: Learning Categories from Examples and Definitions. CogSci 2019: 2406-2412 - [c26]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: 2891-2897 - [c25]Fred Morstatter, Aram Galstyan, Gleb Satyukov, Daniel Benjamin, Andrés Abeliuk, Mehrnoosh Mirtaheri, K. S. M. 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: 6557-6559 - 2018
- [j19]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): 1925-1944 (2018) - 2017
- [j18]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): 476-487 (2017) - [c24]Stephen Bennett, Aaron S. Benjamin, Mark Steyvers:
A Bayesian model of knowledge and metacognitive control: Applications to opt-in tasks. CogSci 2017 - [c23]Brent Miller, Mark Steyvers:
Leveraging Response Consistency within Individuals to Improve Group Accuracy for Rank-Ordering Problems. CogSci 2017 - 2016
- [j17]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: 96-115 (2016) - 2015
- [c22]Michael D. Lee, Emily Liu, Mark Steyvers:
The Roles of Knowledge and Memory in Generating Top-10 Lists. CogSci 2015 - 2014
- [j16]Brandon M. Turner, Mark Steyvers, Edgar C. Merkle, David V. Budescu, Thomas S. Wallsten:
Forecast aggregation via recalibration. Mach. Learn. 95(3): 261-289 (2014) - [j15]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): 2465-2492 (2014) - [c21]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 - 2013
- [j14]Edgar C. Merkle, Mark Steyvers:
Choosing a Strictly Proper Scoring Rule. Decis. Anal. 10(4): 292-304 (2013) - [j13]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: 193-206 (2013) - [c20]Sean Tauber, Mark Steyvers:
Inferring Subjective Prior Knowledge: An Integrative Bayesian Approach. CogSci 2013 - [c19]Qiang Liu, Alexander Ihler, Mark Steyvers:
Scoring Workers in Crowdsourcing: How Many Control Questions are Enough? NIPS 2013: 1914-1922 - 2012
- [j12]Sheng Kung Michael Yi, Mark Steyvers, Michael D. Lee, Matthew J. Dry:
The Wisdom of the Crowd in Combinatorial Problems. Cogn. Sci. 36(3): 452-470 (2012) - [j11]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): 498-516 (2012) - [j10]Lisa Pearl, Mark Steyvers:
Detecting authorship deception: a supervised machine learning approach using author writeprints. Lit. Linguistic Comput. 27(2): 183-196 (2012) - [j9]Timothy N. Rubin, America Chambers, Padhraic Smyth, Mark Steyvers:
Statistical topic models for multi-label document classification. Mach. Learn. 88(1-2): 157-208 (2012) - [j8]Michael D. Lee, Mark Steyvers, Mindy de Young, Brent Miller:
Inferring Expertise in Knowledge and Prediction Ranking Tasks. Top. Cogn. Sci. 4(1): 151-163 (2012) - [c18]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 - [c17]Nicole Beckage, Mark Steyvers, Carter T. Butts:
Route choice in individuals - semantic network navigation. CogSci 2012 - [i3]Michal Rosen-Zvi, Thomas L. Griffiths, Mark Steyvers, Padhraic Smyth:
The Author-Topic Model for Authors and Documents. CoRR abs/1207.4169 (2012) - 2011
- [j7]Michael D. Lee, Shunan Zhang, Miles Munro, Mark Steyvers:
Psychological models of human and optimal performance in bandit problems. Cogn. Syst. Res. 12(2): 164-174 (2011) - [j6]Mark Steyvers, Padhraic Smyth, Chaitanya Chemudugunta:
Combining Background Knowledge and Learned Topics. Top. Cogn. Sci. 3(1): 18-47 (2011) - [c16]Michael D. Lee, Mark Steyvers, Mindy de Young, Brent Miller:
A Model-Based Approach to Measuring Expertise in Ranking Tasks. CogSci 2011 - [c15]Brent Miller, Mark Steyvers:
The Wisdom of Crowds with Communication. CogSci 2011 - [c14]Timothy N. Rubin, Matthew D. Zeigenfuse, Mark Steyvers:
A Model of Concept Generalization and Feature Representation in Hierarchies. CogSci 2011 - [c13]Sean Tauber, Mark Steyvers:
Using Inverse Planning and Theory of Mind for Social Goal Inference. CogSci 2011 - [c12]Edgar C. Merkle, Mark Steyvers:
A Psychological Model for Aggregating Judgments of Magnitude. SBP 2011: 236-243 - [i2]Timothy N. Rubin, America Chambers, Padhraic Smyth, Mark Steyvers:
Statistical Topic Models for Multi-Label Document Classification. CoRR abs/1107.2462 (2011) - 2010
- [j5]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): 4:1-4:38 (2010) - [c11]America Chambers, Padhraic Smyth, Mark Steyvers:
Learning concept graphs from text with stick-breaking priors. NIPS 2010: 334-342
2000 – 2009
- 2009
- [j4]Sheng Kung Michael Yi, Mark Steyvers, Michael D. Lee:
Modeling Human Performance in Restless Bandits with Particle Filters. J. Probl. Solving 2(2) (2009) - [j3]Pernille Hemmer, Mark Steyvers:
A Bayesian Account of Reconstructive Memory. Top. Cogn. Sci. 1(1): 189-202 (2009) - [c10]Mark Steyvers, Michael D. Lee, Brent Miller, Pernille Hemmer:
The Wisdom of Crowds in the Recollection of Order Information. NIPS 2009: 1785-1793 - 2008
- [c9]Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyvers:
Combining concept hierarchies and statistical topic models. CIKM 2008: 1469-1470 - [c8]Chaitanya Chemudugunta, America Holloway, Padhraic Smyth, Mark Steyvers:
Modeling Documents by Combining Semantic Concepts with Unsupervised Statistical Learning. ISWC 2008: 229-244 - [i1]Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyvers:
Text Modeling using Unsupervised Topic Models and Concept Hierarchies. CoRR abs/0808.0973 (2008) - 2006
- [c7]David Newman, Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyvers:
Analyzing Entities and Topics in News Articles Using Statistical Topic Models. ISI 2006: 93-104 - [c6]Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyvers:
Modeling General and Specific Aspects of Documents with a Probabilistic Topic Model. NIPS 2006: 241-248 - 2005
- [j2]Mark Steyvers, Joshua B. Tenenbaum:
The Large-Scale Structure of Semantic Networks: Statistical Analyses and a Model of Semantic Growth. Cogn. Sci. 29(1): 41-78 (2005) - [c5]Mark Steyvers, Scott D. Brown:
Prediction and Change Detection. NIPS 2005: 1281-1288 - 2004
- [c4]Mark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, Thomas L. Griffiths:
Probabilistic author-topic models for information discovery. KDD 2004: 306-315 - [c3]Thomas L. Griffiths, Mark Steyvers, David M. Blei, Joshua B. Tenenbaum:
Integrating Topics and Syntax. NIPS 2004: 537-544 - [c2]Michal Rosen-Zvi, Thomas L. Griffiths, Mark Steyvers, Padhraic Smyth:
The Author-Topic Model for Authors and Documents. UAI 2004: 487-494 - 2003
- [j1]Mark Steyvers, Joshua B. Tenenbaum, Eric-Jan Wagenmakers, Ben Blum:
Inferring causal networks from observations and interventions. Cogn. Sci. 27(3): 453-489 (2003) - 2002
- [c1]Thomas L. Griffiths, Mark Steyvers:
Prediction and Semantic Association. NIPS 2002: 11-18
Coauthor Index
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last updated on 2024-11-15 19:34 CET by the dblp team
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