diff --git a/ax/generators/torch/botorch_modular/acquisition.py b/ax/generators/torch/botorch_modular/acquisition.py
index e258051225a..fd8e7421c7f 100644
--- a/ax/generators/torch/botorch_modular/acquisition.py
+++ b/ax/generators/torch/botorch_modular/acquisition.py
@@ -11,7 +11,8 @@
 
 .. [Daulton2026bonsai]
     S. Daulton, D. Eriksson, M. Balandat, and E. Bakshy. BONSAI: Bayesian
-    Optimization with Natural Simplicity and Interpretability. ArXiv, 2026.
+    Optimization with Natural Simplicity and Interpretability. Advances in Neural
+    Information Processing Systems 39 (NeurIPS), 2026.
 """
 
 from __future__ import annotations
diff --git a/tutorials/bonsai/bonsai.ipynb b/tutorials/bonsai/bonsai.ipynb
index 02f41a8c982..d774715712e 100644
--- a/tutorials/bonsai/bonsai.ipynb
+++ b/tutorials/bonsai/bonsai.ipynb
@@ -23,7 +23,7 @@
         "\n",
         "This combination is particularly powerful for high-dimensional problems with low effective dimensionality.\n",
         "\n",
-        "These methods were proposed in **[Daulton, et al. BONSAI: Bayesian Optimization with Natural Simplicity and Interpretability, ArXiv, 2026](https://arxiv.org/abs/2602.07144)**."
+        "These methods were proposed in **[Daulton, et al. BONSAI: Bayesian Optimization with Natural Simplicity and Interpretability. Advances in Neural Information Processing Systems 39 (NeurIPS), 2026](https://arxiv.org/abs/2602.07144)**."
       ]
     },
     {