Williamson, Sinead

20 publications

ICLR 2026 BED-LLM: Intelligent Information Gathering with LLMs and Bayesian Experimental Design Deepro Choudhury, Sinead Williamson, Adam Golinski, Ning Miao, Freddie Bickford Smith, Michael Kirchhof, Yizhe Zhang, Tom Rainforth

TMLR 2026 ExpertLens: Activation Steering Features Are Highly Interpretable Masha Fedzechkina, Eleonora Gualdoni, Sinead Williamson, Katherine Metcalf, Skyler Seto, Barry-John Theobald

ICLR 2026 SelfReflect: Can LLMs Communicate Their Internal Answer Distribution? Michael Kirchhof, Luca Füger, Adam Golinski, Eeshan Gunesh Dhekane, Arno Blaas, Seong Joon Oh, Sinead Williamson

ICLR 2026 To Infinity and Beyond: Tool-Use Unlocks Length Generalization in State Space Models Eran Malach, Omid Saremi, Sinead Williamson, Arwen Bradley, Aryo Lotfi, Emmanuel Abbe, Joshua M. Susskind, Etai Littwin

ICLR 2026 Trained on Tokens, Calibrated on Concepts: The Emergence of Semantic Calibration in LLMs Preetum Nakkiran, Arwen Bradley, Adam Golinski, Eugene Ndiaye, Michael Kirchhof, Sinead Williamson

ICML 2025 Beyond Sensor Data: Foundation Models of Behavioral Data from Wearables Improve Health Predictions Eray Erturk, Fahad Kamran, Salar Abbaspourazad, Sean Jewell, Harsh Sharma, Yujie Li, Sinead Williamson, Nicholas J Foti, Joseph Futoma

NeurIPSW 2024 Efficient and Effective Uncertainty Quantification for LLMs Miao Xiong, Andrea Santilli, Michael Kirchhof, Adam Golinski, Sinead Williamson

NeurIPSW 2024 On a Spurious Interaction Between Uncertainty Scores and Answer Evaluation Metrics in Generative QA Tasks Andrea Santilli, Miao Xiong, Michael Kirchhof, Pau Rodriguez, Federico Danieli, Xavier Suau, Luca Zappella, Sinead Williamson, Adam Golinski

ICMLW 2023 Nonparametric Posterior Normalizing Flows Evan Ott, Sinead Williamson

NeurIPSW 2022 Spike-and-Slab Probabilistic Backpropagation: When Smarter Approximations Make No Difference Evan Ott, Sinead Williamson

IJCAI 2020 Certifai: A Toolkit for Building Trust in AI Systems Jette Henderson, Shubham Sharma, Alan H. Gee, Valeri Alexiev, Steve Draper, Carlos Marin, Yessel Hinojosa, Christine Draper, Michael Perng, Luis Aguirre, Michael Li, Sara Rouhani, Shorya Consul, Susan Michalski, Akarsh Prasad, Mayank Chutani, Aditya Kumar, Shahzad Alam, Prajna Kandarpa, Binnu Jesudasan, Colton Lee, Michael Criscolo, Sinead Williamson, Matt Sanchez, Joydeep Ghosh

AISTATS 2020 Distributed, Partially Collapsed MCMC for Bayesian Nonparametrics Kumar Avinava Dubey, Michael Zhang, Eric Xing, Sinead Williamson

UAI 2014 Parallel Markov Chain Monte Carlo for Pitman-Yor Mixture Models Kumar Avinava Dubey, Sinead Williamson, Eric P. Xing

AISTATS 2013 A Unifying Representation for a Class of Dependent Random Measures Nicholas J. Foti, Joseph D. Futoma, Daniel N. Rockmore, Sinead Williamson

ICML 2013 Parallel Markov Chain Monte Carlo for Nonparametric Mixture Models Sinead Williamson, Avinava Dubey, Eric Xing

ICML 2012 Modeling Images Using Transformed Indian Buffet Processes Ke Zhai, Yuening Hu, Jordan L. Boyd-Graber, Sinead Williamson

NeurIPS 2012 Slice Sampling Normalized Kernel-Weighted Completely Random Measure Mixture Models Nicholas Foti, Sinead Williamson

AISTATS 2010 Dependent Indian Buffet Processes Sinead Williamson, Peter Orbanz, Zoubin Ghahramani

ICML 2010 The IBP Compound Dirichlet Process and Its Application to Focused Topic Modeling Sinead Williamson, Chong Wang, Katherine A. Heller, David M. Blei

ICML 2008 Statistical Models for Partial Membership Katherine A. Heller, Sinead Williamson, Zoubin Ghahramani