Update README.md

README.md

@@ -1,3 +1,62 @@
 ---
 license: mit
+task_categories:
+- question-answering
+- multiple-choice
+language:
+- en
+tags:
+- evaluation
+- responsibleAI
+- utility
+size_categories:
+- 10K<n<100K
 ---
+
+# UtilityBench: Measuring Language Model Utility When Errors Have Different Costs
+
+<p align="left">
+  <a href="https://github.com/LQF39466/UtilityBench"><img src="https://img.shields.io/badge/GitHub-Code-181717?logo=github" alt="GitHub"></a>
+</p>
+
+## Introduction
+
+As language models are increasingly deployed in real-world scenarios with important outcomes, their mistakes can have consequences that correctness alone does not capture. A minor error in a low-stakes question and a dangerous error in medical advice should not carry the same practical significance. We therefore propose a utility-based evaluation paradigm that explicitly incorporates the varying consequences of errors, encouraging more responsible model behavior. As an early trial of this paradigm, we construct UtilityBench with continuous, sample-specific consequence annotations and introduce UtilityAUC.
+
+## Usage
+
+Import to your project using huggingface dataset, or refer to the [github repository](https://github.com/LQF39466/UtilityBench) for an end-to-end demo.
+
+## Dataset Fields
+
+The dataset contains 15,000 records in a single `test` split.
+
+| Field | Type | Description |
+|---|---|---|
+| `id` | int64 | Unique record identifier |
+| `input` | string | Full prompt sent to the model |
+| `answerability` | int8 | 1 = answerable; 0 = refusal required |
+| `reference_answer` | string / null | Reference answer; null for refusal-required prompts |
+| `source_id` | string | Source dataset and item identifier |
+| `eta` | float64 | Relative error-consequence score; higher means greater consequences |
+| `L` | float64 | Positive cost of an incorrect answer |
+| `evaluator_id` | string | Evaluation rule or code-test identifier |
+
+## Acknowledgement
+
+UtilityBench builds on 18 source datasets. We thank their authors for making these resources publicly available. Record-level provenance is preserved in `source_id`.
+
+<!-- ## Citations
+
+If you find this work useful, please consider citing:
+
+```bibtex
+@misc{utilitybench,
+  title={UtilityBench},
+  url={https://github.com/LQF39466/UtilityBench},
+}
+``` -->
+
+## Contact
+
+If you encounter any problems using the dataset or evaluating your models, please [open an issue](https://github.com/LQF39466/UtilityBench/issues) in the github repository.