Card: dataset citation, ParseBench --dataset llamaindex/BooBench and repetition make

README.md

@@ -87,10 +87,10 @@ Boo Bench runs with the [ParseBench](https://github.com/run-llama/ParseBench) CL
 ```bash
 pip install parse-bench            # or: uv tool install parse-bench
 
-parse-bench run llamaparse_agentic --dataset boo                # downloads to ./data/boo, runs, scores, opens the report
-parse-bench run llamaparse_agentic --dataset boo --group script # one room: real, trap, ghost or script
-parse-bench download --dataset boo
-parse-bench status --dataset boo
+parse-bench run llamaparse_agentic --dataset llamaindex/BooBench                # downloads to ./data/boobench, runs, scores
+parse-bench run llamaparse_agentic --dataset llamaindex/BooBench --group script # one room: real, trap, ghost or script
+parse-bench download --dataset llamaindex/BooBench
+parse-bench status --dataset llamaindex/BooBench
 ```
 
 The score is the rule pass rate: the share of pages with no Boo, overall and per room.
@@ -98,11 +98,11 @@ The score is the rule pass rate: the share of pages with no Boo, overall and per
 ### On your own documents
 
 ```bash
-parse-bench boo make ./my_docs                         # writes <name>.test.json next to every PDF
+parse-bench repetition make ./my_docs                  # writes <name>.test.json next to every PDF
 parse-bench run llamaparse_agentic --input_dir ./my_docs
 ```
 
-`boo make` reads each PDF's text layer and writes one `repetition_overshoot` rule budgeted from it, the way the
+`repetition make` reads each PDF's text layer and writes one `repetition_overshoot` rule budgeted from it, the way the
 `real` room was built. A PDF without a text layer is skipped (`--scans` tests it as a page that repeats nothing).
 
 ## The rule: `repetition_overshoot`
@@ -198,17 +198,17 @@ The rows follow the ParseBench format, one per page:
 
 ## License and citation
 
-Apache 2.0, like ParseBench. The `real` pages are single pages of publicly available documents. If you use Boo Bench,
-please cite ParseBench:
+Apache 2.0, like ParseBench. The `real` pages are single pages of publicly available documents. There is no paper
+yet; if you use Boo Bench, please cite the dataset:
 
 ```bibtex
-@misc{zhang2026parsebench,
-      title={ParseBench: A Document Parsing Benchmark for AI Agents},
-      author={Boyang Zhang and Sebastián G. Acosta and Preston Carlson and Sacha Bron and Pierre-Loïc Doulcet and Simon Suo},
+@misc{doulcet2026boobench,
+      title={Boo Bench: A Haunted House for Document Parsers},
+      author={Pierre-Loïc Doulcet},
       year={2026},
-      eprint={2604.08538},
-      archivePrefix={arXiv},
-      primaryClass={cs.CV},
-      url={https://arxiv.org/abs/2604.08538},
+      publisher={Hugging Face},
+      howpublished={\url{https://huggingface.co/datasets/llamaindex/BooBench}},
 }
 ```
+
+It runs on [ParseBench](https://github.com/run-llama/ParseBench).