Paper Citation Record · LEDGER

SOREL-20M: A Large Scale Benchmark Dataset for Malicious PE Detection

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2012.07634.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2012.07634 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T11:21:31.557319Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-06-30T12:54:40.517639Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 9820717a-1045-4613-be87-3de3d5d9d5ba · inbound

ClarAVy: A Tool for Scalable and Accurate Malware Family Labeling cites this paper.

ClarAVy: A Tool for Scalable and Accurate Malware Family Labeling SOREL-20M: A Large Scale Benchmark Dataset for Malicious PE Detection

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-09T11:21:31.557319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df0c8fdd-37a4-4a6f-8a17-49de10378fd2 · inbound

EMBER2024 -- A Benchmark Dataset for Holistic Evaluation of Malware Classifiers cites this paper.

EMBER2024 -- A Benchmark Dataset for Holistic Evaluation of Malware Classifiers SOREL-20M: A Large Scale Benchmark Dataset for Malicious PE Detection

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:13.779822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51756964-aff3-4601-987b-a4fe76c5cfec · inbound

Adaptive Malware Detection using Sequential Feature Selection: A Dueling Double Deep Q-Network (D3QN) Framework for Intelligent Classification cites this paper.

Adaptive Malware Detection using Sequential Feature Selection: A Dueling Double Deep Q-Network (D3QN) Framework for Intelligent Classification SOREL-20M: A Large Scale Benchmark Dataset for Malicious PE Detection

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T19:53:59.522211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9fcd705c-f2b2-4f70-ba42-34b7310e9add · inbound

Trident: Improving Malware Detection with LLMs and Behavioral Features cites this paper.

Trident: Improving Malware Detection with LLMs and Behavioral Features SOREL-20M: A Large Scale Benchmark Dataset for Malicious PE Detection

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:36:10.587462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a0f0fb49-874b-4b43-88d2-9ca181043e6b · inbound

LCC-LLM: Leveraging Code-Centric Large Language Models for Malware Attribution cites this paper.

LCC-LLM: Leveraging Code-Centric Large Language Models for Malware Attribution SOREL-20M: A Large Scale Benchmark Dataset for Malicious PE Detection

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:21:08.531350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4ed3504b-4c02-49cf-a580-1b63a6767a51 · inbound

Cybersecurity is the True Frontier for Generative AI Success or Failure cites this paper.

Cybersecurity is the True Frontier for Generative AI Success or Failure SOREL-20M: A Large Scale Benchmark Dataset for Malicious PE Detection

Reference 91

Resolution: verified exact; arxiv_id, observed 2026-06-30T12:54:40.519091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.