Update README.md

README.md

@@ -20,13 +20,13 @@ configs:
         path: queries/test*
 ---
 
-The dataset **CapRetrieval** introduced in [Dense Retrievers Can Fail on Simple Queries: Revealing The Granularity Dilemma of Embeddings](https://arxiv.org/abs/2506.08592).
+The dataset **CapRetrieval** introduced in the EMNLP 2025 Finding paper: [[Dense Retrievers Can Fail on Simple Queries: Revealing The Granularity Dilemma of Embeddings](https://arxiv.org/abs/2506.08592)].
 
-**CapRetrieval** is prepared in Chinese; the English version of CapRetrieval is available at [CapRetrievalEn](https://huggingface.co/datasets/lxucs/CapRetrievalEn), sharing the same queries, passages and labels.
+**CapRetrieval** is in Chinese; the according English version is available at [CapRetrievalEn](https://huggingface.co/datasets/lxucs/CapRetrievalEn), sharing the same queries, passages and labels.
 
 ### Introduction
 
-CapRetrieval evaluates the fine-grained embedding matching (dense passage retrieval) in Chinese, tailored towards a practical image search scenario:
+CapRetrieval evaluates the fine-grained embedding matching (dense passage retrieval), tailored towards a practical image search scenario:
 - Candidate passages are image captions, and queries are short phrases of entities or events reflected in captions.
 - Overall, the dataset comprises seemingly simple queries and captions; however, text encoders are shown limitations resolving these cases.
 - Evaluation results call for attention on embedding training strategies with different **granularity**. 
@@ -68,14 +68,14 @@ The trained models (based on `bge-base-zh-v1.5`) are trained with queries by our
 ### Citation
 
 ```bibtex
-@misc{xu2025denseretrieversfailsimple,
-      title={Dense Retrievers Can Fail on Simple Queries: Revealing The Granularity Dilemma of Embeddings}, 
-      author={Liyan Xu and Zhenlin Su and Mo Yu and Jiangnan Li and Fandong Meng and Jie Zhou},
-      year={2025},
-      eprint={2506.08592},
-      archivePrefix={arXiv},
-      primaryClass={cs.CL},
-      url={https://arxiv.org/abs/2506.08592}, 
+@inproceedings{xu-etal-2025-dense,
+    title = "Dense Retrievers Can Fail on Simple Queries: Revealing The Granularity Dilemma of Embeddings",
+    author = "Xu, Liyan and Su, Zhenlin and Yu, Mo and Li, Jiangnan and Meng, Fandong and Zhou, Jie",
+    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2025",
+    month = nov,
+    year = "2025",
+    address = "Suzhou, China",
+    publisher = "Association for Computational Linguistics"
 }
 ```