Link paper: arXiv:2608.05224 (COLM'26) + citation

README.md

@@ -41,7 +41,7 @@ pretty_name: Psych-201 Reaction Time Dataset
 
 # Psych-201 Reaction Time Dataset
 
-A curated dataset of human reaction time (RT) measurements extracted from [Psych-201](https://github.com/marcelbinz/Psych-201), a large-scale collection of naturalistic language transcriptions of human psychology experiments. The dataset is designed for modeling individual-level response latency distributions across diverse experimental paradigms.
+A curated dataset of human reaction time (RT) measurements extracted from [Psych-201](https://github.com/marcelbinz/Psych-201), a large-scale collection of naturalistic language transcriptions of human psychology experiments. The dataset is designed for modeling individual-level response latency distributions across diverse experimental paradigms. Introduced in [*Small Foundation Models of Human Cognition and Behaviour*](https://arxiv.org/abs/2608.05224) (COLM'26).
 
 ## Dataset Summary
 
@@ -94,4 +94,18 @@ print(f"Mean RT: {sum(sample['RTs']) / len(sample['RTs']):.3f}s")
 
 This dataset is derived from:
 
-> Binz et al. (2025). Psych-201. *[GitHub](https://github.com/marcelbinz/Psych-201)*.
+> Binz et al. (2025). Psych-201. *[GitHub](https://github.com/marcelbinz/Psych-201)*.
+
+## Citation
+
+If you use this dataset, please cite:
+
+```bibtex
+@inproceedings{oh2026smallcogfm,
+  title     = {Small Foundation Models of Human Cognition and Behaviour},
+  author    = {Oh, Nick and Gobet, Fernand},
+  booktitle = {Third Conference on Language Modeling (COLM)},
+  year      = {2026},
+  note      = {arXiv:2608.05224}
+}
+```