Paper Citation Record · LEDGER

Lightweight Vulnerability Detection from Code Metrics and Token Features

As of 11 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2605.04260.

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

pith.paper-citation-record.v1
2605.04260 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-08T17:24:03.424290Z

measured 21 of 21 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

21 of 21 outbound references displayed

verified exact2
verified fuzzy19
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3faaf239-eae5-4ac7-8801-f8443eb24608 · outbound

This paper cites Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks.

Lightweight Vulnerability Detection from Code Metrics and Token Features Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:36:06.642488Z

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 9d60e6fb-4050-4a90-a29b-5bf72e32d577 · outbound

This paper cites The Precision-Recall Plot Is More Informative than the ROC Plot When Evaluating Binary Classifiers on Imbalanced Datasets.

Lightweight Vulnerability Detection from Code Metrics and Token Features The Precision-Recall Plot Is More Informative than the ROC Plot When Evaluating Binary Classifiers on Imbalanced Datasets

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T07:56:55.303430Z

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 14287a4c-7488-439a-babb-6bf664b7af3f · outbound

This paper cites Predicting Vulnerable Software Components.

Lightweight Vulnerability Detection from Code Metrics and Token Features Predicting Vulnerable Software Components

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T07:56:55.307049Z

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 52d0be69-71fa-44e0-a7d4-3dc81f5b5cbc · outbound

This paper cites Predicting Vulnerable Software Components via Text Mining.

Lightweight Vulnerability Detection from Code Metrics and Token Features Predicting Vulnerable Software Components via Text Mining

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T07:56:55.299244Z

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 03405a8f-faaa-440b-8e6e-2b5b119d2225 · outbound

This paper cites The Relationship Between Precision-Recall and ROC Curves.

Lightweight Vulnerability Detection from Code Metrics and Token Features The Relationship Between Precision-Recall and ROC Curves

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T07:56:55.315675Z

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 db25fe2e-c2d4-497a-9a0a-bce341e67bf7 · outbound

This paper cites Learning from Imbalanced Data.

Lightweight Vulnerability Detection from Code Metrics and Token Features Learning from Imbalanced Data

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T07:56:55.328490Z

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 1e757203-7aac-47b5-a863-db63f3204cdf · outbound

This paper cites Static Analysis for Security.

Lightweight Vulnerability Detection from Code Metrics and Token Features Static Analysis for Security

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T07:56:55.339706Z

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 85881e09-04b6-41ec-9ff4-a1dfd168172c · outbound

This paper cites ITS4: A Static Vulnerability Scanner for C and C++ Code.

Lightweight Vulnerability Detection from Code Metrics and Token Features ITS4: A Static Vulnerability Scanner for C and C++ Code

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T07:56:55.319708Z

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 9520c212-f632-488c-abd6-36a639ed6867 · outbound

This paper cites Flawfinder.

Lightweight Vulnerability Detection from Code Metrics and Token Features Flawfinder

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T07:56:55.343343Z

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 02a75928-7b1d-4e7d-955c-77a9ab86f120 · outbound

This paper cites Searching for a Needle in a Haystack: Predicting Security Vulnerabilities for Windows Vista.

Lightweight Vulnerability Detection from Code Metrics and Token Features Searching for a Needle in a Haystack: Predicting Security Vulnerabilities for Windows Vista

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T07:56:55.347241Z

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 62401a46-6504-4e1b-a917-742033a79347 · outbound

This paper cites Evaluating Complexity, Code Churn, and Developer Activity Metrics as Indicators of Software Vulnerabilities.

Lightweight Vulnerability Detection from Code Metrics and Token Features Evaluating Complexity, Code Churn, and Developer Activity Metrics as Indicators of Software Vulnerabilities

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T07:56:55.324256Z

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 97416f57-2f1b-4eea-8db8-a7a969b82ebd · outbound

This paper cites Is Complexity Really the Enemy of Software Security?.

Lightweight Vulnerability Detection from Code Metrics and Token Features Is Complexity Really the Enemy of Software Security?

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T07:56:55.336126Z

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 54c21494-8012-4118-91a3-7262755a668d · outbound

This paper cites Prioritizing Software Security Fortification through Code-Level Metrics.

Lightweight Vulnerability Detection from Code Metrics and Token Features Prioritizing Software Security Fortification through Code-Level Metrics

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T07:56:55.332241Z

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 f641e1ed-da41-4b9f-a5f4-2c419d17d6df · outbound

This paper cites VulDeePecker: A Deep Learning-Based System for Vulnerability Detection.

Lightweight Vulnerability Detection from Code Metrics and Token Features VulDeePecker: A Deep Learning-Based System for Vulnerability Detection

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T07:56:55.351037Z

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 25efba66-1dac-4837-bf87-7c3fd87264f1 · outbound

This paper cites SySeVR: A Framework for Using Deep Learning to Detect Software Vulnerabilities.

Lightweight Vulnerability Detection from Code Metrics and Token Features SySeVR: A Framework for Using Deep Learning to Detect Software Vulnerabilities

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-08T20:09:07.742798Z

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 275c9830-6093-4413-8269-361fc6e87367 · outbound

This paper cites VUDDY: A Scalable Approach for Vulnerable Code Clone Discovery.

Lightweight Vulnerability Detection from Code Metrics and Token Features VUDDY: A Scalable Approach for Vulnerable Code Clone Discovery

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T07:56:55.311478Z

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 6cb62ad7-9ed1-4904-be4d-9506ffc821ab · outbound

This paper cites VCCFinder: Finding Potential Vulnerabilities in Open-Source Projects to Assist Code Audits.

Lightweight Vulnerability Detection from Code Metrics and Token Features VCCFinder: Finding Potential Vulnerabilities in Open-Source Projects to Assist Code Audits

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T07:56:55.290632Z

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 9491f579-27a7-4cc7-a857-1e5ce66152e1 · outbound

This paper cites Predicting Vulnerable Components: Software Metrics vs. Text Mining.

Lightweight Vulnerability Detection from Code Metrics and Token Features Predicting Vulnerable Components: Software Metrics vs. Text Mining

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T07:56:55.283162Z

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 f9392b34-6b75-471b-a284-c0b8b898e42b · outbound

This paper cites To Fear or Not to Fear That is the Question: Code Characteristics of a Vulnerable Function with an Existing Exploit.

Lightweight Vulnerability Detection from Code Metrics and Token Features To Fear or Not to Fear That is the Question: Code Characteristics of a Vulnerable Function with an Existing Exploit

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T07:56:55.279310Z

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 0f3a4018-409d-447b-9aad-47668f74bfd9 · outbound

This paper cites Term-Weighting Approaches in Automatic Text Retrieval.

Lightweight Vulnerability Detection from Code Metrics and Token Features Term-Weighting Approaches in Automatic Text Retrieval

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T07:56:55.294882Z

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 80eb2f7e-d315-4f0c-86ee-a0974cd9f2f7 · outbound

This paper cites Scikit-learn: Machine Learning in Python.

Lightweight Vulnerability Detection from Code Metrics and Token Features Scikit-learn: Machine Learning in Python

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T07:56:55.286854Z

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.

Pith citing papers

No inbound Pith citation observations are available.