# RAP Benchmark Dataset Card

## Task

RAP evaluates whether an agent can estimate the distribution of newly posted
papers across eight operational research directions and forecast the
distribution in the following six months. Each episode uses `forecast_date=T`
as its boundary. The history windows describe the available past periods and
the future window is `[T, T+6 months)`.

The State task estimates the distribution observed in the most recent
six-month window. The Forecast task predicts the distribution in the next
six-month window.

## Package contents

- `inputs/` contains the model-facing Dev/Test episode inputs.
- `targets/` contains evaluator-only recent and future counts, shares, and
  diagnostics.
- `evaluator/` contains combined episode records for scoring and offline
  baselines.
- `data/` contains the frozen evaluation scope and Search-manifest indexes.
- `search_shards/` contains the metadata-only Search snapshot.

Each row in `inputs/` contains the field, cutoff date, time-window metadata,
and eight direction definitions. It does not contain history counts, recent
shares, future counts, or future shares. Those evaluator-only values are stored
in `targets/` and `evaluator/`.

## Splits and evaluation

Dev and Test are frozen field-level splits rather than random episode-level
splits. Dev contains 335 episodes from 67 fields; Test contains 1,055 episodes
from 211 fields. The evaluation-code repository provides the prompt protocol,
scorer, contract checks, and offline statistical baselines.

Target shares are normalized across the eight directions, using primary-direction
counts. Direction definitions and episode boundaries are provided in each input
record. Use `inputs/` for agent runs and `targets/` or `evaluator/` for scoring.

## Search snapshot

`search_shards/fixed/` enforces the window `[T-6m, T)`, while
`search_shards/expanding/` enforces `<T`. Each shard contains exactly
`id`, `date`, `title`, `abstract`, and `categories`. The shard manifests record
SHA-256 digests, row counts, and date-bound checks.

The Search snapshot contains descriptive arXiv metadata only. See
`ARXIV_METADATA_NOTICE.md` for provenance and source terms.

## Integrity

From the dataset root, run:

```bash
sha256sum -c SHA256SUMS
```

## License

This repository is marked `other` because it combines original RAP-derived
artifacts with arXiv descriptive metadata. Read `LICENSE` and
`ARXIV_METADATA_NOTICE.md` before redistribution or adaptation.

## Citation

```bibtex
@misc{wu2026rap,
  title  = {RAP: Research Attention Prediction Reveals Target-Conditioned Evidence Acquisition Biases},
  author = {Wu, Yingqian and Liang, Jingcong and Wang, Siyuan and Yin, Zhenfei
            and Torr, Philip and Yu, Junchi and Wei, Zhongyu},
  year   = {2026},
  url    = {https://arxiv.org/abs/2609.10092}
}
```