license: other
configs:
- config_name: arxiv
data_files:
- split: papers
path: arxiv/*.parquet
- config_name: openreview-iclr
data_files:
- split: papers
path: iclr/*.parquet
tags:
- academic-paper-review
- paper-review
- sharegpt
- text
language:
- en
size_categories:
- 100K<n<1M
pl-text-nips
Text version of the OpenReview-ICLR and arXiv PaperLens datasets. Anonymous release for double-blind review.
Each row is one unique paper. We release all extracted papers — not every
paper here is used in our downstream training/eval sets. The papers that are
used are denoted by the references field, which lists every internal
(release_name, release_split) pair the paper belongs to (a single paper can
belong to multiple). The accompanying reconstruction.py in the anonymous code
release reads this field to materialize the original sharegpt data.json for
any of the publishable text keys.
Configs (subsets)
arxiv— papers from arXiv (per_venue + 21k families + residual + the arXiv side of combined).openreview-iclr— papers from ICLR via OpenReview (balanced_original + max_rejects + train_50pct/75pct + the iclr side of combined).
from datasets import load_dataset
ds_arxiv = load_dataset("anonuser231357/pl-text-nips", "arxiv", split="papers")
ds_iclr = load_dataset("anonuser231357/pl-text-nips", "openreview-iclr", split="papers")
Schema
| field | type | description |
|---|---|---|
paper_id |
string |
arXiv id or OpenReview submission id |
title |
string |
paper title |
content |
string |
prompt-stripped body (the full paper body in markdown) |
metadata |
string |
JSON blob — venue, year, authors, ratings, decision, … |
label |
string |
"Accept" or "Reject" |
references |
list<list<string>> |
each entry is [release_name, release_split] — the internal splits this paper belongs to |
Reconstructing the sharegpt data.json files
reconstruction.py (in the anonymous code release) rebuilds any of the
publishable internal keys (e.g. arxiv_50_50_21k_text_..._y24up_test)
byte-identically from this dataset. Point --hf_text_repo at this repo:
python scripts/reconstruction.py \
--hf_text_repo anonuser231357/pl-text-nips \
--dataset_keys arxiv_50_50_balanced_per_venue_text_wmetadata_filtered24480_train
Reconstructed files land in ./data/ by default (override with --data_root <path>):
data/<dataset_key>/data.json (sharegpt rows) and data/dataset_info.json
(LlamaFactory entry).
The release ships a manifest.json sidecar mapping each internal
dataset_info.json key → (release_name, release_split, columns, file_name),
so reconstruction reproduces conversations, _metadata, and
accept_reject_label (where applicable).
License & citation
License: other. Citation withheld for anonymous review.