Corpus Data & Downloads

This public snapshot contains 478,991 papers and8,981,698 citation edges. The exports were generated from ClickHouse and are available as raw JSON under CC-BY 4.0. The operator corpus may be newer.

478,991
Papers ingested
8,981,698
Citation edges
511,313
Abstracts stored
1.5 GB
Compressed size

Sources

arxiv
399,902
78.2% of corpus
biorxiv
63,752
12.5% of corpus
openreview
30,327
5.9% of corpus
medrxiv
17,332
3.4% of corpus

106,595 peer reviews aggregated from OpenReview venues. Average paper size: 3.0 kB.

Papers per year (recent)

2026
380
2025
4,712
2024
25,662
2023
32,591
2022
32,436
2021
40,418
2020
50,744
2019
42,617

Top semantic communities

50 communities detected from citation graph structure. Each has anchor papers and topic labels.

cluster #024,393 papers
ADADELTA: An Adaptive Learning Rate Method
languagelearningneuralmodels
cluster #118,493 papers
Very Deep Convolutional Networks for Large-Scale Image Recognition
learningsegmentationobjectdeep
cluster #217,101 papers
Improving neural networks by preventing co-adaptation of feature detectors
learningneuraldeepnetworks
cluster #314,639 papers
Adam: A Method for Stochastic Optimization
imagelearninggenerativedeep
cluster #413,568 papers
Quantum computers
quantumqubitmmlsuperconducting
cluster #510,478 papers
Fast large-scale optimization by unifying stochastic gradient and quasi-Newton methods
learningfederatedfederated learningprivacy
cluster #69,992 papers
Playing Atari with Deep Reinforcement Learning
learningreinforcementreinforcement learningplanning
cluster #79,435 papers
Advances in quantum metrology
quantumentanglementstatesmml

Downloadable JSON exports

All files are served from /data/*.json and licensed CC-BY 4.0. Cite as: researchPapers OpenAlex CS Corpus Analytics, papers.highsignal.app/data.

FileDescriptionDownload
summary.jsonCorpus ingest summary: paper counts, edge counts, storage sizeJSON
top_papers.jsonTop 200 papers by PageRank and Katz centralityJSON
top_cited_works.jsonMost-cited works across the corpusJSON
hot.json100 hot papers: citation velocity, review rating, and PageRankJSON
sleepers.json100 reviewer-loved early papers with low citation countsJSON
communities.json64 semantic communities with anchor papers and labelsJSON
embedding_clusters.jsonEmbedding cluster assignments from MiniLMJSON
temporal.jsonPapers per year, cites per year, and top paper per yearJSON
tag_rating.jsonMean reviewer rating by extracted topicJSON
tag_cooccurrence.jsonTopic tag co-occurrence matrixJSON
review_venues.jsonPeer-review venue summaries and review countsJSON
review_rating_distribution.jsonRating distribution per review venueJSON
ch_sources_summary.jsonPaper counts by source: arXiv, OpenReview, bioRxiv, and medRxivJSON
top_authors.jsonMost prolific authors in the corpusJSON
top_hosts.jsonTop hosting domains for paper URLsJSON
cycles.jsonCitation cycle detection resultsJSON
abstract_clusters.jsonAbstract-level clustering resultsJSON
host_categories.jsonHost URL categorizationJSON

Data provenance

Papers are sourced from OpenAlex (Computer Science, cited ≥1000). Citation edges are computed from OpenAlex reference lists. Peer-review signals come from OpenReview (ICLR, NeurIPS, ICML, COLM). Semantic search uses all-MiniLM-L6-v2 embeddings stored in ClickHouse. The full pipeline runs via scripts/in the repository.

Public-site analytics

PostHog measures bounded product events and Microsoft Clarity measures aggregate usage and session replay on this public, no-account research library. The semantic-search and cited-answer sections are explicitly masked, so their query text and rendered results are not uploaded to Clarity.

When server-side App Health telemetry is configured, it records only the method, fixed route, response status, and latency for matched public API routes. It does not receive search questions, paper identifiers, request or response content, IP addresses, or user identity.