Andreas Stuhlmüller

According to our database, Andreas Stuhlmüller authored at least 20 papers between 2011 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Factored Verification: Detecting and Reducing Hallucination in Summaries of Academic Papers.

Charlie George, Andreas Stuhlmüller

CoRR, 2023

Iterated Decomposition: Improving Science Q&A by Supervising Reasoning Processes.

Justin Reppert, Ben Rachbach, Charlie George, Luke Stebbing, JungWon Byun, Maggie Appleton, Andreas Stuhlmüller

CoRR, 2023

2022

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models.

Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R. Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, Agnieszka Kluska, Aitor Lewkowycz, Akshat Agarwal, Alethea Power, Alex Ray, Alex Warstadt, Alexander W. Kocurek, Ali Safaya, Ali Tazarv, Alice Xiang, Alicia Parrish, Allen Nie, Aman Hussain, Amanda Askell, Amanda Dsouza, Ameet Rahane, Anantharaman S. Iyer, Anders Andreassen, Andrea Santilli, Andreas Stuhlmüller, Andrew M. Dai, Andrew La, Andrew K. Lampinen, Andy Zou, Angela Jiang, Angelica Chen, Anh Vuong, Animesh Gupta, Anna Gottardi, Antonio Norelli, Anu Venkatesh, Arash Gholamidavoodi, Arfa Tabassum, Arul Menezes, Arun Kirubarajan, Asher Mullokandov, Ashish Sabharwal, Austin Herrick, Avia Efrat, Aykut Erdem, Ayla Karakas, et al.

CoRR, 2022

2021

RAFT: A Real-World Few-Shot Text Classification Benchmark.

Neel Alex, Eli Lifland, Lewis Tunstall, Abhishek Thakur, Pegah Maham, C. Jess Riedel, Emmie Hine, Carolyn Ashurst, Paul Sedille, Alexis Carlier, Michael Noetel, Andreas Stuhlmüller

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

2018

Evaluating Compositionality in Sentence Embeddings.

Ishita Dasgupta, Demi Guo, Andreas Stuhlmüller, Samuel Gershman, Noah D. Goodman

Proceedings of the 40th Annual Meeting of the Cognitive Science Society, 2018

Trial without Error: Towards Safe Reinforcement Learning via Human Intervention.

William Saunders, Girish Sastry, Andreas Stuhlmüller, Owain Evans

Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

2017

Agent-Agnostic Human-in-the-Loop Reinforcement Learning.

David Abel, John Salvatier, Andreas Stuhlmüller, Owain Evans

CoRR, 2017

2016

C3: Lightweight Incrementalized MCMC for Probabilistic Programs using Continuations and Callsite Caching.

Daniel Ritchie, Andreas Stuhlmüller, Noah D. Goodman

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Learning the Preferences of Ignorant, Inconsistent Agents.

Owain Evans, Andreas Stuhlmüller, Noah D. Goodman

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Coarse-to-Fine Sequential Monte Carlo for Probabilistic Programs.

Andreas Stuhlmüller, Robert X. D. Hawkins, N. Siddharth, Noah D. Goodman

CoRR, 2015

Why do you ask? Good questions provoke informative answers.

Robert X. D. Hawkins, Andreas Stuhlmüller, Judith Degen, Noah D. Goodman

Proceedings of the 37th Annual Meeting of the Cognitive Science Society, 2015

2014

Reasoning about reasoning by nested conditioning: Modeling theory of mind with probabilistic programs.

Andreas Stuhlmüller, Noah D. Goodman

Cogn. Syst. Res., 2014

Learning physical theories from dynamical scenes.

Tomer D. Ullman, Andreas Stuhlmüller, Noah D. Goodman, Joshua B. Tenenbaum

Proceedings of the 36th Annual Meeting of the Cognitive Science Society, 2014

2013

Knowledge and Implicature: Modeling Language Understanding as Social Cognition.

Noah D. Goodman, Andreas Stuhlmüller

Top. Cogn. Sci., 2013

Learning Stochastic Inverses.

Andreas Stuhlmüller, Jessica Taylor, Noah D. Goodman

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2012

A Dynamic Programming Algorithm for Inference in Recursive Probabilistic Programs.

Andreas Stuhlmüller, Noah D. Goodman

Proceedings of the 2nd International Workshop on Statistical Relational AI (StaRAI-12), 2012

Probabilistic generative models for counterfactual reasoning and blame attribution.

John McCoy, Tomer D. Ullman, Andreas Stuhlmüller, Tobias Gerstenberg, Joshua B. Tenenbaum

Proceedings of the 34th Annual Meeting of the Cognitive Science Society, 2012

2011

Lightweight Implementations of Probabilistic Programming Languages Via Transformational Compilation.

David Wingate, Andreas Stuhlmüller, Noah D. Goodman

Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Inducing Probabilistic Programs by Bayesian Program Merging

Irvin Hwang, Andreas Stuhlmüller, Noah D. Goodman

CoRR, 2011

Nonstandard Interpretations of Probabilistic Programs for Efficient Inference.

David Wingate, Noah D. Goodman, Andreas Stuhlmüller, Jeffrey Mark Siskind

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011