diff --git a/docs/papers.md b/docs/papers.md
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@@ -18,6 +18,20 @@ The main reference for BoTorch is
 
 Here is an incomplete selection of peer-reviewed Bayesian optimization papers that build off of BoTorch:
 
+- [Robust Gaussian Processes via Relevance Pursuit](https://arxiv.org/abs/2410.24222). Sebastian Ament, David Eriksson, Elizabeth Santorella, Ben Letham, Max Balandat, Eytan Bakshy. NeurIPS 2024.
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+- [Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes](https://arxiv.org/abs/2407.09739). Syrine Belakaria, Ben Letham, Janardhan R. Doppa, Barbara Engelhardt, Stefano Ermon, Eytan Bakshy. NeurIPS 2024.
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+- [Approximation-Aware Bayesian Optimization](https://arxiv.org/abs/2406.04308). Natalie Maus, Kyurae Kim, Geoff Pleiss, David Eriksson, John P. Cunningham, Jacob R. Gardner. NeurIPS 2024.
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+- [Bayesian Optimization of Function Networks with Partial Evaluations](https://arxiv.org/abs/2311.02146). Poompol Buathong, Jiayue Wan, Raul Astudillo, Sam Daulton, Maximilian Balandat, Peter I. Frazier. ICML 2024.
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+- [Joint Composite Latent Space Bayesian Optimization](https://arxiv.org/abs/2311.02213). Natalie Maus, Zhiyuan Jerry Lin, Maximilian Balandat, Eytan Bakshy. ICML 2024.
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+- [Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo is All you Need](https://arxiv.org/abs/2402.02111). Shangda Yang, Vitaly Zankin, Maximilian Balandat, Stefan Scherer, Kevin Thomas Carlberg, Neil Walton, Kody J. H. Law. ICML 2024.
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+- [Response Time Improves Choice Prediction and Function Estimation for Gaussian Process Models of Perception and Preferences](https://arxiv.org/abs/2306.06296). Michael Shvartsman, Benjamin Letham, Stephen Keeley. UAI 2024.
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 - [Advancing Bayesian Optimization via Learning Correlated Latent Space](https://arxiv.org/pdf/2310.20258.pdf). Seunghun Lee, Jaewon Chu, Sihyeon Kim, Juyeon Ko, Hyunwoo J. Kim. NeurIPS 2023.
 
 - [Unexpected Improvements to Expected Improvement for Bayesian Optimization](https://arxiv.org/abs/2310.20708). Sebastian Ament, Samuel Daulton, David Eriksson, Maximilian Balandat, Eytan Bakshy. NeurIPS 2023.