Update README.md

README.md

@@ -93,7 +93,7 @@ BOOM series exhibit substantially higher spectral entropy, indicating greater ir
 Principal Component Analysis (PCA) applied to the full feature set (Figure 1) reveals a clear separation between BOOM and [GiftEval](https://huggingface.co/datasets/Salesforce/GiftEval) datasets. BOOM occupies a broader and more dispersed region of the feature space, reflecting greater diversity in signal complexity and temporal structure. This separation reinforces the benchmark’s relevance for evaluating models under realistic, deployment-aligned conditions.
 
 ## Links:
-  - [Research Paper](https://www.datadoghq.com/pdf/blog/opentoto_v2.pdf)
+  - [Research Paper](https://arxiv.org/abs/2505.14766)
   - [Codebase](https://github.com/DataDog/toto)
   - [Leaderboard 🏆](https://huggingface.co/spaces/Datadog/BOOM)
   - [Toto model (Datadog's open-weights model with state-of-the-art performance on BOOM)](https://huggingface.co/Datadog/Toto-Open-Base-1.0)