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README.md

@@ -30,10 +30,7 @@ configs:
 
 **A Benchmark for Detail Hallucination in Long Regulatory Documents**
 
-DetailBench is a benchmark for evaluating and mitigating *detail hallucination* in LLM outputs on long regulatory documents. It accompanies the paper:
-
-> **DetailDPO: Targeted Preference Optimization for Reducing Detail Hallucination in Long Regulatory Documents**
-> (EMNLP 2026)
+DetailBench is a benchmark for evaluating and mitigating *detail hallucination* in LLM outputs on long regulatory documents.
 
 ## Overview
 
@@ -157,17 +154,6 @@ print(len(sample["documents"]))
 
 Error type distribution in the training set is balanced at 20% each (2,000 per type).
 
-## Citation
-
-```bibtex
-@inproceedings{detaildpo2026,
-  title={DetailDPO: Targeted Preference Optimization for Reducing Detail Hallucination in Long Regulatory Documents},
-  author={...},
-  booktitle={Proceedings of EMNLP 2026},
-  year={2026}
-}
-```
-
 ## License
 
 This dataset is released under CC-BY-4.0. The underlying regulatory documents are sourced from public government repositories (eCFR, EUR-Lex, openstd.samr.gov.cn).