Add arXiv link and citation

README.md

@@ -20,7 +20,7 @@ configs:
 
 # RAGCompass data
 
-Per-retriever results and passage corpora for the paper *RAGCompass: Generalizable Retriever Routing via Reranking*. Code: [github.com/Graph-COM/RAGCompass](https://github.com/Graph-COM/RAGCompass).
+Per-retriever results and passage corpora for the paper [*RAGCompass: Generalizable Retriever Routing via Reranking*](https://arxiv.org/abs/2611.05596). Code: [github.com/Graph-COM/RAGCompass](https://github.com/Graph-COM/RAGCompass).
 
 For every query, each of five retrievers returned its top-5 passages, and a fixed reader (`meta-llama/Llama-3.1-8B-Instruct`) answered from them. The F1 of that answer is the utility a retriever router is trained to predict. The data covers 4 datasets x 3 splits x 5 retrievers x 5,000 queries, plus the passage corpus of every split, so routing methods can be trained and evaluated without rerunning retrieval or the reader.
 
@@ -73,9 +73,12 @@ The data is derived from Natural Questions (CC BY-SA 3.0), HotpotQA (CC BY-SA 4.
 
 ```bibtex
 @misc{six2026ragcompass,
-  title  = {RAGCompass: Generalizable Retriever Routing via Reranking},
-  author = {Six, Valentin and Li, Mufei and Fu, Dongqi and Xia, Yinglong and Li, Hong and Li, Pan},
-  year   = {2026},
-  note   = {Preprint}
+  title         = {RAGCompass: Generalizable Retriever Routing via Reranking},
+  author        = {Six, Valentin and Li, Mufei and Fu, Dongqi and Xia, Yinglong and Li, Hong and Li, Pan},
+  year          = {2026},
+  eprint        = {2611.05596},
+  archivePrefix = {arXiv},
+  primaryClass  = {cs.CL},
+  url           = {https://arxiv.org/abs/2611.05596}
 }
 ```