Add dataset card and metadata

README.md

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+---
+license: mit
+task_categories:
+- text-retrieval
+tags:
+- agentic-search
+- bm25
+---
+
+# Pi-Serini
+
+This repository contains data and artifacts associated with the paper [Rethinking Agentic Search with Pi-Serini: Is Lexical Retrieval Sufficient?](https://huggingface.co/papers/2605.10848).
+
+Pi-Serini is a reusable, benchmark-driven search-agent workspace designed for index-driven BM25 retrieval, agentic search, and benchmark-aware evaluation. It revisits whether a lexical retriever (BM25) suffices when paired with capable frontier Large Language Models (LLMs) in an agentic loop.
+
+- **Project Page:** [https://ricky42613.github.io/piserini](https://ricky42613.github.io/piserini)
+- **GitHub Repository:** [https://github.com/justram/pi-serini](https://github.com/justram/pi-serini)
+
+## Supported Benchmarks
+
+The Pi-Serini framework supports several benchmarks for evaluation:
+- `browsecomp-plus`: Default packaged benchmark used to evaluate deep research capabilities.
+- `msmarco-v1-passage`: Index-driven MS MARCO v1 passage benchmark.
+- `benchmark-template`: A tiny local end-to-end demo benchmark for validation.
+
+## Citation
+
+```bibtex
+@misc{hsu2026rethinkingagenticsearchpiserini,
+  title         = {Rethinking Agentic Search with Pi-Serini: Is Lexical Retrieval Sufficient?},
+  author        = {Tz-Huan Hsu and Jheng-Hong Yang and Jimmy Lin},
+  year          = {2026},
+  eprint        = {2605.10848},
+  archivePrefix = {arXiv},
+  primaryClass  = {cs.IR},
+  url           = {https://arxiv.org/abs/2605.10848}
+}
+```