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README.md

@@ -3,35 +3,52 @@ configs:
 - config_name: default
   data_files:
   - split: law
-    path: "law.json"
+    path: law.json
   - split: psychology
-    path: "psychology.json"
+    path: psychology.json
   - split: chemistry
-    path: "chemistry.json"
+    path: chemistry.json
   - split: biology
-    path: "biology.json"
+    path: biology.json
   - split: physics
-    path: "physics.json"
+    path: physics.json
   - split: history
-    path: "history.json"
+    path: history.json
   - split: economics
-    path: "economics.json"
+    path: economics.json
   - split: math
-    path: "math.json"
+    path: math.json
   - split: business
-    path: "business.json"
+    path: business.json
   - split: philosophy
-    path: "philosophy.json"
+    path: philosophy.json
   - split: health
-    path: "health.json"
+    path: health.json
   - split: engineering
-    path: "engineering.json"
+    path: engineering.json
   - split: computer_science
-    path: "computer_science.json"
+    path: computer_science.json
   - split: other
-    path: "other.json"
+    path: other.json
+task_categories:
+- text-ranking
+language:
+- en
+tags:
+- reward-model
+- multi-domain
+- llm-evaluation
 ---
-# Reward of [test](https://huggingface.co/datasets/dongboklee/test) split extracted by dORM-8B: dORM-8B-test
+
+# Rethinking Reward Models for Multi-Domain Test-Time Scaling
+
+This dataset contains reward scores for the `test` split, extracted by the `dORM-8B` model. It is part of the research presented in the paper "Rethinking Reward Models for Multi-Domain Test-Time Scaling", which assesses the reliability of large language models using reward models across 14 diverse domains.
+
+**Paper:** [Rethinking Reward Models for Multi-Domain Test-Time Scaling](https://huggingface.co/papers/2510.00492)
+**Code:** [https://github.com/db-Lee/Multi-RM](https://github.com/db-Lee/Multi-RM)
+
+## Reward of [test](https://huggingface.co/datasets/dongboklee/test) split extracted by dORM-8B: dORM-8B-test
+
 ## Usage
 ```python
 from datasets import load_dataset
@@ -40,3 +57,13 @@ dataset = load_dataset("dongboklee/dORM-8B-test")
 # Load specific domain
 law_dataset = load_dataset("dongboklee/dORM-8B-test", split="law")
 ```
+
+## Citation
+```bibtex
+@article{multi-rm,
+  title   = {Rethinking Reward Models for Multi-Domain Test-Time Scaling},
+  author  = {Lee, Dong Bok and Lee, Seanie and Park, Sangwoo and Kang, Minki and Baek, Jinheon and Kim, Dongki and Wagner, Dominik and Jin, Jiongdao and Lee, Heejun and Bocklet, Tobias and Wang, Jinyu and Fu, Jingjing and Hwang, Sung Ju and Bian, Jiang and Song, Lei},
+  journal = {arXiv preprint arXiv:2510.00492},
+  year    = {2025}
+}
+```