Fetching the paper…
Reading the bibliography…
What do we want from machine intelligence? We envision machines that are not just tools for thought, but partners in thought: reasonable, insightful, knowledgeable, reliable, and trustworthy systems that think with us.
Technics and civilization
Lewis Mumford · 1936
Earlier work this paper cites.
Computing machinery and intelligence
Alan Turing · 1950
Earlier work this paper cites.
Cyborgs and space
Manfred E Clynes and Nathan S Kline · 1960
Earlier work this paper cites.
Eliza—a computer program for the study of natural language communication between man and machine
Joseph Weizenbaum · 1966
Earlier work this paper cites.
Human problem solving
Allen Newell and Herbert A. Simon · 1972
Earlier work this paper cites.
Availability: A heuristic for judging frequency and probability
Amos Tversky and Daniel Kahneman · 1973
Earlier work this paper cites.
Judgment under uncertainty: Heuristics and biases: Biases in judgments reveal some heuristics of thinking under uncertainty
Amos Tversky and Daniel Kahneman · 1974
Earlier work this paper cites.
Logic and conversation
Herbert P Grice · 1975
Earlier work this paper cites.
Computer power and human reason: From judgment to calculation
Joseph Weizenbaum · 1976
Earlier work this paper cites.
A cognitive process theory of writing
Linda Flower and John R. Hayes · 1981
Earlier work this paper cites.
The computer modelling of mathematical reasoning
Alan Bundy · 1983
Earlier work this paper cites.
Mental models: Towards a cognitive science of language, inference, and consciousness
Philip Nicholas Johnson-Laird · 1983
Earlier work this paper cites.
The lisp tutor
John R Anderson and Brian J Reiser · 1985
Earlier work this paper cites.
Design Of Everyday Things
Don Norman · 1988
Earlier work this paper cites.
Cognitive modeling and intelligent tutoring
John R Anderson, C Franklin Boyle, Albert T Corbett, and Matthew W Lewis · 1990
Earlier work this paper cites.
The adaptive character of thought
John R Anderson · 1990
Earlier work this paper cites.
Inductive logic programming: Theory and methods
Stephen Muggleton and Luc De Raedt · 1994
Earlier work this paper cites.
Cognitive tutors: Lessons learned
John R Anderson, Albert T Corbett, Kenneth R Koedinger, and Ray Pelletier · 1995
Earlier work this paper cites.
Bayesian modeling of human concept learning
Joshua Tenenbaum · 1998
Earlier work this paper cites.
Core knowledge
Elizabeth S Spelke · 2000
Earlier work this paper cites.
Mental models and counterfactual thoughts about what might have been
Ruth MJ Byrne · 2002
Earlier work this paper cites.
Human-robot interactions during the robot-assisted urban search and rescue response at the world trade center
Jennifer Casper and Robin R. Murphy · 2003
Earlier work this paper cites.
Hierarchical topic models and the nested chinese restaurant process
Thomas Griffiths, Michael Jordan, Joshua Tenenbaum, and David Blei · 2003
Earlier work this paper cites.
Designing the whyline: a debugging interface for asking questions about program behavior
Amy J Ko and Brad A Myers · 2004
Earlier work this paper cites.
Object perception as bayesian inference
Daniel Kersten, Pascal Mamassian, and Alan Yuille · 2004
Earlier work this paper cites.
Integrating topics and syntax
Thomas Griffiths, Mark Steyvers, David Blei, and Joshua Tenenbaum · 2004
Earlier work this paper cites.
A theory of causal learning in children: causal maps and bayes nets
Alison Gopnik, Clark Glymour, David M Sobel, Laura E Schulz, and Tamar et al Kushnir · 2004
Earlier work this paper cites.
The Cambridge handbook of thinking and reasoning
Keith J Holyoak and Robert G Morrison · 2005
Earlier work this paper cites.
Probabilistic models of language processing and acquisition
Nick Chater and Christopher D Manning · 2006
Earlier work this paper cites.
Bayesian rationality: The probabilistic approach to human reasoning
Mike Oaksford and Nick Chater · 2007
Earlier work this paper cites.
Word learning as bayesian inference
Fei Xu and Joshua B Tenenbaum · 2007
Earlier work this paper cites.
Can being scared cause tummy aches? naive theories, ambiguous evidence, and preschoolers’ causal inferences
Laura E Schulz, Elizabeth Baraff Bonawitz, and Thomas L Griffiths · 2007
Earlier work this paper cites.
The Probabilistic Mind: Prospects for Bayesian Cognitive Science
Nick Chater and Mike Oaksford, editors · 2008
Earlier work this paper cites.
Bayesian models of cognition
Thomas L. Griffiths, Charles Kemp, and Joshua B. Tenenbaum · 2008
Earlier work this paper cites.
The discovery of structural form
Charles Kemp and Joshua B Tenenbaum · 2008
Earlier work this paper cites.
The tractable cognition thesis
Iris Van Rooij · 2008
Earlier work this paper cites.
Action understanding as inverse planning
Chris L Baker, Rebecca Saxe, and Joshua B Tenenbaum · 2009
Earlier work this paper cites.
A bayesian account of reconstructive memory
Pernille Hemmer and Mark Steyvers · 2009
Earlier work this paper cites.
Theory-based causal induction
Thomas L Griffiths and Joshua B Tenenbaum · 2009
Earlier work this paper cites.
How to grow a mind: Statistics, structure, and abstraction
Joshua B Tenenbaum, Charles Kemp, Thomas L Griffiths, and Noah D Goodman · 2011
Earlier work this paper cites.
The state of the art in end-user software engineering
Amy J Ko, Robin Abraham, Laura Beckwith, Alan Blackwell, and Margaret et al Burnett · 2011
Earlier work this paper cites.
Bayesian theory of mind: Modeling joint belief-desire attribution
Chris Baker, Rebecca Saxe, and Joshua Tenenbaum · 2011
Earlier work this paper cites.
The Oxford handbook of thinking and reasoning
Keith J Holyoak and Robert G Morrison · 2012
Earlier work this paper cites.
Modeling and remodeling writing
John R Hayes · 2012
Earlier work this paper cites.
Pomcop: Belief space planning for sidekicks in cooperative games
Owen Macindoe, Leslie Pack Kaelbling, and Tomás Lozano-Pérez · 2012
Earlier work this paper cites.
Predicting pragmatic reasoning in language games
Michael C Frank and Noah D Goodman · 2012
Earlier work this paper cites.
Generalized grounding graphs: A probabilistic framework for understanding grounded language
Thomas Kollar, Stefanie Tellex, Matthew R Walter, Albert Huang, and Abraham et al Bachrach · 2013
Earlier work this paper cites.
Shared agency: A planning theory of acting together
Michael E Bratman · 2013
Earlier work this paper cites.
Legibility and predictability of robot motion
Anca D Dragan, Kenton CT Lee, and Siddhartha S Srinivasa · 2013
Earlier work this paper cites.
Simulation as an engine of physical scene understanding
Peter W Battaglia, Jessica B Hamrick, and Joshua B Tenenbaum · 2013
Earlier work this paper cites.
Causal responsibility and counterfactuals
David A Lagnado, Tobias Gerstenberg, and Ro’i Zultan · 2013
Earlier work this paper cites.
Knowledge and implicature: Modeling language understanding as social cognition
Noah D Goodman and Andreas Stuhlmüller · 2013
Earlier work this paper cites.
Concepts in a probabilistic language of thought
Noah D Goodman, Joshua B Tenenbaum, and Tobias Gerstenberg · 2014
Earlier work this paper cites.
One and done? optimal decisions from very few samples
Edward Vul, Noah Goodman, Thomas L Griffiths, and Joshua B Tenenbaum · 2014
Earlier work this paper cites.
Selecting computations: Theory and applications
Nicholas Hay, Stuart Russell, David Tolpin, and Solomon Eyal Shimony · 2014
Earlier work this paper cites.
Modeling human plan recognition using bayesian theory of mind
Chris L Baker and Joshua B Tenenbaum · 2014
Earlier work this paper cites.
A rational account of pedagogical reasoning: Teaching by, and learning from, examples
Patrick Shafto, Noah D Goodman, and Thomas L Griffiths · 2014
Earlier work this paper cites.
Tutorons: Generating context-relevant, on-demand explanations and demonstrations of online code
Andrew Head, Codanda Appachu, Marti A Hearst, and Björn Hartmann · 2015
Earlier work this paper cites.
Human-level concept learning through probabilistic program induction
Brenden M Lake, Ruslan Salakhutdinov, and Joshua B Tenenbaum · 2015
Earlier work this paper cites.
Probabilistic semantics and pragmatics uncertainty in language and thought
Noah D Goodman and Daniel Lassiter · 2015
Earlier work this paper cites.
A resource-rational approach to the causal frame problem
Thomas Icard and Noah D Goodman · 2015
Earlier work this paper cites.
Algorithm aversion: people erroneously avoid algorithms after seeing them err
Berkeley J Dietvorst, Joseph P Simmons, and Cade Massey · 2015
Earlier work this paper cites.
Pragmatic language interpretation as probabilistic inference
Noah D Goodman and Michael C Frank · 2016
Earlier work this paper cites.
The naïve utility calculus: Computational principles underlying commonsense psychology
Julian Jara-Ettinger, Hyowon Gweon, Laura E Schulz, and Joshua B Tenenbaum · 2016
Earlier work this paper cites.
The logical primitives of thought: Empirical foundations for compositional cognitive models
Steven T Piantadosi, Joshua B Tenenbaum, and Noah D Goodman · 2016
Earlier work this paper cites.
Cooperative inverse reinforcement learning
Dylan Hadfield-Menell, Stuart J Russell, Pieter Abbeel, and Anca Dragan · 2016
Earlier work this paper cites.
Concrete problems in ai safety
Dario Amodei, Chris Olah, Jacob Steinhardt, Paul Christiano, and John et al Schulman · 2016
Earlier work this paper cites.
Deep reinforcement learning from human preferences
Paul F Christiano, Jan Leike, Tom Brown, Miljan Martic, and Shane et al Legg · 2017
Earlier work this paper cites.
Building machines that learn and think like people
Brenden M. Lake, Tomer D. Ullman, Joshua B. Tenenbaum, and Samuel J. Gershman · 2017
Earlier work this paper cites.
Capability-based task allocation in human-robot collaboration
Fabian Ranz, Vera Hummel, and Wilfried Sihn · 2017
Earlier work this paper cites.
The relationship between physician burnout and quality of healthcare in terms of safety and acceptability: a systematic review
Carolyn S Dewa, Desmond Loong, Sarah Bonato, and Lucy Trojanowski · 2017
Earlier work this paper cites.
Towards a rigorous science of interpretable machine learning
Finale Doshi-Velez and Been Kim · 2017
Earlier work this paper cites.
Transparent role assignment and task allocation in human robot collaboration
Alessandro Roncone, Olivier Mangin, and Brian Scassellati · 2017
Earlier work this paper cites.
Rational quantitative attribution of beliefs, desires and percepts in human mentalizing
Chris L Baker, Julian Jara-Ettinger, Rebecca Saxe, and Joshua B Tenenbaum · 2017
Earlier work this paper cites.
European union regulations on algorithmic decision-making and a “right to explanation”
Bryce Goodman and Seth Flaxman · 2017
Earlier work this paper cites.
Unintended consequences of machine learning in medicine
Federico Cabitza, Raffaele Rasoini, and Gian Franco Gensini · 2017
Earlier work this paper cites.
What is interaction?
Kasper Hornbæk and Antti Oulasvirta · 2017
Earlier work this paper cites.
Turing: a language for flexible probabilistic inference
Hong Ge, Kai Xu, and Zoubin Ghahramani · 2018
Earlier work this paper cites.
Where do you think you’re going?: Inferring beliefs about dynamics from behavior
Sid Reddy, Anca Dragan, and Sergey Levine · 2018
Earlier work this paper cites.
A systematic literature review of automated feedback generation for programming exercises
Hieke Keuning, Johan Jeuring, and Bastiaan Heeren · 2018
Cited alongside, same era.
Recasting gradient-based meta-learning as hierarchical bayes
Erin Grant, Chelsea Finn, Sergey Levine, Trevor Darrell, and Thomas Griffiths · 2018
Cited alongside, same era.
Probabilistic programming with programmable inference
Vikash K Mansinghka, Ulrich Schaechtle, Shivam Handa, Alexey Radul, Yutian Chen, and Martin Rinard · 2018
Cited alongside, same era.
An outline of a theory of affordances
Anthony Chemero · 2018
Cited alongside, same era.
Overcoming algorithm aversion: People will use imperfect algorithms if they can (even slightly) modify them
Berkeley J Dietvorst, Joseph P Simmons, and Cade Massey · 2018
Cited alongside, same era.
Gen: a general-purpose probabilistic programming system with programmable inference
Rational use of cognitive resources in human planning
Frederick Callaway, Bas van Opheusden, Sayan Gul, Priyam Das, and Paul M et al Krueger · 2022
Later among the works it cites.
Scalable Structure Learning, Inference, and Analysis with Probabilistic Programs
Feras Ahmad Khaled Saad · 2022
Later among the works it cites.
Ai-assisted decision-making: A cognitive modeling approach to infer latent reliance strategies
Heliodoro Tejeda, Aakriti Kumar, Padhraic Smyth, and Mark Steyvers · 2022
Later among the works it cites.
Bayesian modeling of human–ai complementarity
Mark Steyvers, Heliodoro Tejeda, Gavin Kerrigan, and Padhraic Smyth · 2022
Later among the works it cites.
Non-dyadic interaction: A literature review of 15 years of human-robot interaction conference publications
Eike Schneiders, EunJeong Cheon, Jesper Kjeldskov, Matthias Rehm, and Mikael B Skov · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Marco F Cusumano-Towner, Feras A Saad, Alexander K Lew, and Vikash K Mansinghka · 2019
Cited alongside, same era.
Pyro: Deep universal probabilistic programming
Eli Bingham, Jonathan P Chen, Martin Jankowiak, Fritz Obermeyer, and Neeraj et al Pradhan · 2019
Cited alongside, same era.
High-performance medicine: the convergence of human and artificial intelligence
Eric J Topol · 2019
Cited alongside, same era.
The proof of the pudding: in praise of a culture of real-world validation for medical artificial intelligence
Federico Cabitza and Jean-David Zeitoun · 2019
Cited alongside, same era.
Explanation in artificial intelligence: Insights from the social sciences
Tim Miller · 2019
Cited alongside, same era.
The promise of artificial intelligence: reckoning and judgment
Brian Cantwell Smith · 2019
Cited alongside, same era.
On the utility of learning about humans for human-ai coordination
Micah Carroll, Rohin Shah, Mark K Ho, Tom Griffiths, and Sanjit et al Seshia · 2019
Cited alongside, same era.
Eva Hornecker, Antonia Krummheuer, Andreas Bischof, and Matthias Rehm · 2022
Later among the works it cites.
Human-level play in the game of diplomacy by combining language models with strategic reasoning
Anton Bakhtin, Noam Brown, Emily Dinan, Gabriele Farina, and Colin et al Flaherty · 2022
Later among the works it cites.
Taxonomy of risks posed by language models
Laura Weidinger, Jonathan Uesato, Maribeth Rauh, Conor Griffin, and Po-Sen et al Huang · 2022
Later among the works it cites.
Large language models fail on trivial alterations to theory-of-mind tasks
Tomer Ullman · 2023
Later among the works it cites.
Lionel Wong, Gabriel Grand, Alexander K Lew, Noah D Goodman, and Vikash K et al Mansinghka · 2023
Later among the works it cites.
Socially intelligent machines that learn from humans and help humans learn
Hyowon Gweon, Judith Fan, and Been Kim · 2023
Later among the works it cites.
R Thomas McCoy, Shunyu Yao, Dan Friedman, Matthew Hardy, and Thomas L Griffiths · 2023
Later among the works it cites.
Bayes in the age of intelligent machines, 2023
Thomas L. Griffiths, Jian-Qiao Zhu, Erin Grant, and R. Thomas McCoy · 2023
Later among the works it cites.
Turning large language models into cognitive models
Marcel Binz and Eric Schulz · 2023
Later among the works it cites.
Expertise increases planning depth in human gameplay
Bas van Opheusden, Ionatan Kuperwajs, Gianni Galbiati, Zahy Bnaya, and Yunqi et al Li · 2023
Later among the works it cites.
Using github copilot to solve simple programming problems
Michel Wermelinger · 2023
Later among the works it cites.
Grounded copilot: How programmers interact with code-generating models
Shraddha Barke, Michael B James, and Nadia Polikarpova · 2023
Later among the works it cites.
Github copilot ai pair programmer: Asset or liability?
Arghavan Moradi Dakhel, Vahid Majdinasab, Amin Nikanjam, Foutse Khomh, and Michel C et al Desmarais · 2023
Later among the works it cites.
Social dynamics of ai support in creative writing
Katy Ilonka Gero, Tao Long, and Lydia B Chilton · 2023
Later among the works it cites.
Navigating the jagged technological frontier: Field experimental evidence of the effects of ai on knowledge worker productivity and quality
Fabrizio Dell’Acqua, Edward McFowland, Ethan R Mollick, Hila Lifshitz-Assaf, and Katherine et al Kellogg · 2023
Later among the works it cites.
Revisiting the time needed to provide adult primary care
Justin Porter, Cynthia Boyd, M Reza Skandari, and Neda Laiteerapong · 2023
Later among the works it cites.
Large language models encode clinical knowledge
Karan Singhal, Shekoofeh Azizi, Tao Tu, S Sara Mahdavi, and Jason et al Wei · 2023
Later among the works it cites.
Comparing Physician and Artificial Intelligence Chatbot Responses to Patient Questions Posted to a Public Social Media Forum
John W. Ayers, Adam Poliak, Mark Dredze, Eric C. Leas, and Zechariah et al Zhu · 2023
Later among the works it cites.
Alignment with human representations supports robust few-shot learning
Ilia Sucholutsky and Thomas L Griffiths · 2023
Later among the works it cites.
Getting aligned on representational alignment, 2023
Ilia Sucholutsky, Lukas Muttenthaler, Adrian Weller, Andi Peng, and Andreea Bobu et al · 2023
Later among the works it cites.
Peano: learning formal mathematical reasoning
Gabriel Poesia and Noah D Goodman · 2023
Later among the works it cites.
Language agents as digital representatives in collective decision-making
Daniel Jarrett, Miruna Pislar, Michiel A Bakker, Michael Henry Tessler, and Raphael et al Koster · 2023
Later among the works it cites.
Improving factuality and reasoning in language models through multiagent debate
Yilun Du, Shuang Li, Antonio Torralba, Joshua B Tenenbaum, and Igor Mordatch · 2023
Later among the works it cites.
Using artificial intelligence in craft education: crafting with text-to-image generative models
Henriikka Vartiainen and Matti Tedre · 2023
Later among the works it cites.
The best game in town: The reemergence of the language-of-thought hypothesis across the cognitive sciences
Jake Quilty-Dunn, Nicolas Porot, and Eric Mandelbaum · 2023
Later among the works it cites.
Resource rationality
Thomas Icard · 2023
Later among the works it cites.
The rational speech act framework
Judith Degen · 2023
Later among the works it cites.
Meta-learned models of cognition
Marcel Binz, Ishita Dasgupta, Akshay K Jagadish, Matthew Botvinick, and Jane X et al Wang · 2023
Later among the works it cites.
Human-like systematic generalization through a meta-learning neural network
Brenden M Lake and Marco Baroni · 2023
Later among the works it cites.
The inner loop of collective human–machine intelligence
Scott Cheng-Hsin Yang, Tomas Folke, and Patrick Shafto · 2023
Later among the works it cites.
Three challenges for ai-assisted decision-making
Mark Steyvers and Aakriti Kumar · 2023
Later among the works it cites.
Lance Ying, Katherine M Collins, Megan Wei, Cedegao E Zhang, and Tan et al Zhi-Xuan · 2023
Later among the works it cites.
Teaching and learning through pedagogical environment design
Emily G Liquin, Nicole Luzuriaga, and Todd M Gureckis · 2023
Later among the works it cites.
Differentiating mental models of self et al: A hierarchical framework for knowledge assessment
Aakriti Kumar, Padhraic Smyth, and Mark Steyvers · 2023
Later among the works it cites.
The autocorrelated bayesian sampler: A rational process for probability judgments, estimates, confidence intervals, choices, confidence judgments, and response times
Jian-Qiao Zhu, Joakim Sundh, Jake Spicer, Nick Chater, and Adam N Sanborn · 2023
Later among the works it cites.
People seek easily interpretable information
Samuel J Cheyette, Frederick Callaway, Neil R Bramley, Jonathan D Nelson, and Josh Tenenbaum · 2023
Later among the works it cites.
Bayes3d: fast learning and inference in structured generative models of 3d objects and scenes
Nishad Gothoskar, Matin Ghavami, Eric Li, Aidan Curtis, and Michael et al Noseworthy · 2023
Later among the works it cites.
Generative ai and chatgpt: Applications, challenges, and ai-human collaboration, 2023
Fiona Fui-Hoon Nah, Ruilin Zheng, Jingyuan Cai, Keng Siau, and Langtao Chen · 2023
Later among the works it cites.
Acting as inverse inverse planning
Kartik Chandra, Tzu-Mao Li, Joshua Tenenbaum, and Jonathan Ragan-Kelley · 2023
Later among the works it cites.
Enhancing the reliability and accuracy of ai-enabled diagnosis via complementarity-driven deferral to clinicians
Krishnamurthy Dvijotham, Jim Winkens, Melih Barsbey, Sumedh Ghaisas, and Robert et al Stanforth · 2023
Later among the works it cites.
Three-dimensional collision avoidance method for robot-assisted minimally invasive surgery
Ling Li, Xiaojian Li, Bo Ouyang, Hangjie Mo, and Hongliang et al Ren · 2023
Later among the works it cites.
Generative agents: Interactive simulacra of human behavior, 2023
Joon Sung Park, Joseph C. O’Brien, Carrie J. Cai, Meredith Ringel Morris, and Percy Liang et al · 2023
Later among the works it cites.
Algorithmic loafing and mitigation strategies in human-ai teams
Isa Inuwa-Dutse, Alice Toniolo, Adrian Weller, and Umang Bhatt · 2023
Later among the works it cites.
Steroids, sneakers, coach: The spectrum of human-ai relationships
Jake M Hofman, Daniel G Goldstein, and David M Rothschild · 2023
Later among the works it cites.
Calibrated language models must hallucinate
Adam Tauman Kalai and Santosh S Vempala · 2023
Later among the works it cites.
Characterizing manipulation from ai systems
Micah Carroll, Alan Chan, Henry Ashton, and David Krueger · 2023
Later among the works it cites.
Ai safety on whose terms?
Seth Lazar and Alondra Nelson · 2023
Later among the works it cites.
Language is primarily a tool for communication rather than thought
Evelina Fedorenko, Steven T Piantadosi, and Edward AF Gibson · 2024
Closest in time.
Evaluating language models for mathematics through interactions
Katherine M Collins, Albert Q Jiang, Simon Frieder, Lionel Wong, and Miri et al Zilka · 2024
Closest in time.
Dissociating language and thought in large language models
Kyle Mahowald, Anna A Ivanova, Idan A Blank, Nancy Kanwisher, and Joshua B et al Tenenbaum · 2024
Closest in time.
Solving olympiad geometry without human demonstrations
Trieu H Trinh, Yuhuai Wu, Quoc V Le, He He, and Thang Luong · 2024
Closest in time.
Tree of thoughts: Deliberate problem solving with large language models
Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, and Tom et al Griffiths · 2024
Closest in time.
Pragmatic instruction following and goal assistance via cooperative language-guided inverse planning
Tan Zhi-Xuan, Lance Ying, Vikash Mansinghka, and Joshua B Tenenbaum · 2024
Closest in time.
It takes two to think
Itai Yanai and Martin J Lercher · 2024
Closest in time.
Do as i can, not as i say: Grounding language in robotic affordances
Michael Ahn, Anthony Brohan, Noah Brown, Yevgen Chebotar, and Omar et al Cortes · 2024
Closest in time.
Scaling instructable agents across many simulated worlds
Maria Abi Raad, Arun Ahuja, Catarina Barros, Frederic Besse, and Andrew et al Bolt · 2024
Closest in time.
Evaluating cognitive maps and planning in large language models with cogeval
Ida Momennejad, Hosein Hasanbeig, Felipe Vieira Frujeri, Hiteshi Sharma, and Nebojsa et al Jojic · 2024
Closest in time.
A design space for intelligent and interactive writing assistants
Mina Lee, Katy Ilonka Gero, John Joon Young Chung, Simon Buckingham Shum, and Vipul et al Raheja · 2024
Closest in time.
Towards conversational diagnostic ai, 2024
Tao Tu, Anil Palepu, Mike Schaekermann, Khaled Saab, and Jan Freyberg et al · 2024
Closest in time.
Gensql: A probabilistic programming system for querying generative models of database tables
Mathieu Huot, Matin Ghavami, Alexander K Lew, Ulrich Schaechtle, and Cameron E et al Freer · 2024
Closest in time.
Automated statistical model discovery with language models
Michael Y Li, Emily B Fox, and Noah D Goodman · 2024
Closest in time.
Mathematical discoveries from program search with large language models
Bernardino Romera-Paredes, Mohammadamin Barekatain, Alexander Novikov, Matej Balog, and M Pawan et al Kumar · 2024
Closest in time.
How ai ideas affect the creativity, diversity, and evolution of human ideas: Evidence from a large, dynamic experiment, 2024
Joshua Ashkinaze, Julia Mendelsohn, Li Qiwei, Ceren Budak, and Eric Gilbert · 2024
Closest in time.
The use of generative search engines for knowledge work and complex tasks
Siddharth Suri, Scott Counts, Leijie Wang, Chacha Chen, and Mengting et al Wan · 2024
Closest in time.
Probabilistic programming with programmable variational inference
McCoy R Becker, Alexander K Lew, Xiaoyan Wang, Matin Ghavami, Mathieu Huot, Martin C Rinard, and Vikash K Mansinghka · 2024
Closest in time.
Artificial intelligence and illusions of understanding in scientific research
Lisa Messeri and MJ Crockett · 2024
Closest in time.
Intervening on emotions by planning over a theory of mind
Tony Chen, Sean Dae Houlihan, Kartik Chandra, Josh Tenenbaum, and Rebecca Saxe · 2024
Closest in time.
Learning generative population models from multiple clinical datasets via probabilistic programming
João Loula, Katherine M Collins, Ulrich Schaechtle, Joshua B Tenenbaum, and Adrian et al Weller · 2024
Closest in time.
Milena Tsvetkova, Taha Yasseri, Niccolo Pescetelli, and Tobias Werner · 2024
Closest in time.
Beyond dyadic interactions: Assessing trust networks in multi-human-robot teams
Aakash Yadav and Ranjana Mehta · 2024
Closest in time.
Representational alignment supports effective machine teaching
Ilia Sucholutsky, Katherine M Collins, Maya Malaviya, Nori Jacoby, and Weiyang et al Liu · 2024
Closest in time.
Interaction structure constrains the emergence of conventions in group communication
Veronica Boyce, Robert D Hawkins, Noah D Goodman, and Michael C Frank · 2024
Closest in time.
Using games to understand the mind
Kelsey Allen, Franziska Brändle, Matthew Botvinick, Judith E Fan, and Samuel J et al Gershman · 2024
Closest in time.