Datasets:
metadata
license: cc-by-4.0
task_categories:
- text-classification
language:
- en
tags:
- SDQP
- scholarly
- citation_count_prediction
- review_score_prediction
dataset_info:
features:
- name: paperhash
dtype: string
- name: s2_corpus_id
dtype: string
- name: arxiv_id
dtype: string
- name: title
dtype: string
- name: abstract
dtype: string
- name: authors
sequence:
- name: name
dtype: string
- name: affiliation
struct:
- name: laboratory
dtype: string
- name: institution
dtype: string
- name: location
dtype: string
- name: summary
dtype: string
- name: field_of_study
sequence: string
- name: venue
dtype: string
- name: publication_date
dtype: string
- name: n_references
dtype: int32
- name: n_citations
dtype: int32
- name: n_influential_citations
dtype: int32
- name: introduction
dtype: string
- name: background
dtype: string
- name: methodology
dtype: string
- name: experiments_results
dtype: string
- name: conclusion
dtype: string
- name: full_text
dtype: string
- name: decision
dtype: bool
- name: decision_text
dtype: string
- name: reviews
sequence:
- name: review_id
dtype: string
- name: review
struct:
- name: title
dtype: string
- name: paper_summary
dtype: string
- name: main_review
dtype: string
- name: strength_weakness
dtype: string
- name: questions
dtype: string
- name: limitations
dtype: string
- name: review_summary
dtype: string
- name: score
dtype: float32
- name: confidence
dtype: float32
- name: novelty
dtype: float32
- name: correctness
dtype: float32
- name: clarity
dtype: float32
- name: impact
dtype: float32
- name: reproducibility
dtype: float32
- name: ethics
dtype: string
- name: comments
sequence:
- name: title
dtype: string
- name: comment
dtype: string
- name: references
sequence:
- name: paperhash
dtype: string
- name: title
dtype: string
- name: abstract
dtype: string
- name: authors
sequence:
- name: name
dtype: string
- name: affiliation
struct:
- name: laboratory
dtype: string
- name: institution
dtype: string
- name: location
dtype: string
- name: arxiv_id
dtype: string
- name: s2_corpus_id
dtype: string
- name: intents
sequence: string
- name: isInfluential
dtype: bool
- name: hypothesis
dtype: string
- name: month_since_publication
dtype: int32
- name: avg_citations_per_month
dtype: float32
- name: mean_score
dtype: float32
- name: mean_confidence
dtype: float32
- name: mean_novelty
dtype: float32
- name: mean_correctness
dtype: float32
- name: mean_clarity
dtype: float32
- name: mean_impact
dtype: float32
- name: mean_reproducibility
dtype: float32
- name: openreview_submission_id
dtype: string
splits:
- name: acl_ocl_train
num_bytes: 2553475339
num_examples: 42060
- name: acl_ocl_validation
num_bytes: 805703352
num_examples: 9013
- name: acl_ocl_test
num_bytes: 806719943
num_examples: 9014
download_size: 2084737209
dataset_size: 4165898634
configs:
- config_name: acl_ocl
data_files:
- split: train
path: data/acl_ocl_train-*
- split: validation
path: data/acl_ocl_validation-*
- split: test
path: data/acl_ocl_test-*
- config_name: openreview-full
data_files:
- split: train
path: data/openreview_full_training-*
- split: validation
path: data/openreview_full_validation-*
- split: test
path: data/openreview_full_test-*
- config_name: openreview-iclr
data_files:
- split: train
path: data/iclr_training-*
- split: validation
path: data/iclr_validation-*
- split: test
path: data/iclr_test
- config_name: default
data_files:
- split: train
path: data/iclr_training-*
- split: validation
path: data/iclr_validation-*
- split: test
path: data/iclr_test-*
- config_name: openreview-iclr
data_files:
- split: train
path: data/iclr_training-*
- split: validation
path: data/iclr_validation-*
- split: test
path: data/iclr_test-*
- config_name: openreview-neurips
data_files:
- split: train
path: data/neurips_training-*
- split: validation
path: data/neurips_validation-*
- split: test
path: data/neurips_test-*
- config_name: openreview-public
data_files:
- split: train
path: data/openreview_public_train-*
- split: validation
path: data/openreview_public_validation-*
- split: test
path: data/openreview_public_test-*
Datasets related to the task of Scholarly Document Quality Prediction (SDQP). Each sample is an academic paper for which either the citation count or the review score can be predicted (depending on availability).
ACL-OCL Extended
A dataset for citation count prediction only, based on the ACL-OCL dataset. Extended with updated citation counts, references and annotated research hypothesis
OpenReview (Last Update: 1.1.2025)
A dataset for review score and citation count prediction, obtained by parsing OpenReview. Due to licensing the dataset comes in different formats:
Datasets without parsed pdfs of submissions (i.e. the fields introduction, background, methodology, experiments_results, conclusion, full_text are available)
- openreview-public: Contains full information on all OpenReview submissions that are accompanied with a CC BY 4.0 license.
Datasets without parsed pdfs of submissions (i.e. the fields introduction, background, methodology, experiments_results, conclusion, full_text are None)
- openreview-full: Contains all OpenReview submissions, splits generated based on publications dates.
- openreview-iclr: All ICLR submissions from the years 2018-2023 (training) and 2024 (validation and training).
- openreview-neurips: All NeurIPS submissions from the years 2021-2023 (training) and 2024 (validation and training).
All datasets without parsed pdfs of submissions can be completed by running code available here