updated readme

README.md

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 ---
+language:
+- en
 license: cc-by-4.0
 ---
+
+## Dataset Information
+
+Most conversational agents (CAs) are designed to satisfy user needs through user-driven interactions. However, many real-world settings, such as academic interviewing, judicial proceedings, and journalistic investigations, involve broader institutional decision-making processes and require agents that can elicit information from users. To enable systematic research on this setting, we present *YIELD*, a 26M-token dataset of 2,281 ethically sourced, human-to-human dialogues. For full details, see the accompanying paper [here](https://doi.org/10.48550/arXiv.2604.10968).
+
+
+## Code Repository
+
+GitHub: https://github.com/infosenselab/yield
+
+
+## Citing YIELD
+
+If you use this resource in your projects, please cite the following paper.
+
+
+```bibtex
+@misc{De_Lima_YIELD_A_Large-Scale_2026,
+author = {De Lima, Victor and Yang, Grace Hui},
+doi = {10.48550/arXiv.2604.10968},
+title = {{YIELD: A Large-Scale Dataset and Evaluation Framework for Information Elicitation Agents}},
+url = {https://arxiv.org/abs/2604.10968},
+year = {2026}
+}
+```