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Paper Citation Record · LEDGER

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection

As of 21 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 8 inbound Pith citation observations for arXiv:2505.19828.

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

pith.paper-citation-record.v1
2505.19828 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:09:03.342895Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T11:02:54.227103Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T07:09:37.546449Z

Reference resolution

25 of 25 outbound references displayed

  • verified exact1
  • verified fuzzy14
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7fda9ac4-0923-414d-b5fd-af4fc7bd09ed · outbound

This paper cites Cvefixes: automated collection of vulner- abilities and their fixes from open-source software.

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection Cvefixes: automated collection of vulner- abilities and their fixes from open-source software

Reference 1

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raw_fallback, observed 2026-08-07T14:09:09.164889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:09:01.065583Z digest=sha256:778a4576e0a8202245285046a8b78a3acbf897a32ac34801aed969c07d56983a

Observation 0b31b96f-8165-4ee0-b0e7-45dccea377f1 · outbound

This paper cites Deep learning based vulnerability detection: Are we there yet? IEEE Transactions on Software Engineering , 48(9):3280–3296, 2021.

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection Deep learning based vulnerability detection: Are we there yet? IEEE Transactions on Software Engineering , 48(9):3280–3296, 2021

Reference 2

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raw_fallback, observed 2026-08-07T14:09:08.796392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:09:01.201054Z digest=sha256:7218283bd74127b8e9616f97c502b5e72140580ba977a1db28365b1058f727c7

Observation 7af37375-ecc7-4c59-8294-3ad0377109a7 · outbound

This paper cites Diversevul: A new vulnerable source code dataset for deep learning based vulnerability detection.

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection Diversevul: A new vulnerable source code dataset for deep learning based vulnerability detection

Reference 3

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raw_fallback, observed 2026-08-07T14:09:08.294753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:09:01.324789Z digest=sha256:406ba4fa4dd47143bc6e6856f4a2dcea0e0dbb551c4497211bfa2590849907cc

Observation 15710a1b-3497-45ba-82dc-51d0a0712e80 · outbound

This paper cites CreativEval: Evaluating Creativity of LLM-Based Hardware Code Generation.

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection CreativEval: Evaluating Creativity of LLM-Based Hardware Code Generation

Reference 4

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local_arxiv, observed 2026-08-07T14:09:04.509343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:09:01.394753Z digest=sha256:42953cfcb5ff16fc82c6255c520ca3fc462f8130f338fe5a8fb3b18ac2110bef

Observation e9dba13b-230c-47a9-b8e2-150acbba3834 · outbound

This paper cites Vulnerability Detection with Code Language Models: How Far Are We?.

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection Vulnerability Detection with Code Language Models: How Far Are We?

Reference 5

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no resolver link, observed 2026-08-07T14:09:01.505613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:09:01.505613Z digest=sha256:e0f0b05523d78b7b7463cd5d4808c4657f4933bfff3d966d3f011af4d546333e

Observation a142ed5f-90e0-425c-824c-05ee848a7b91 · outbound

This paper cites Ac/c++ code vulnerability dataset with code changes and cve summaries.

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection Ac/c++ code vulnerability dataset with code changes and cve summaries

Reference 6

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raw_fallback, observed 2026-08-07T14:09:08.014836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:09:01.594912Z digest=sha256:3771e404e219c7ebefc906dce86d70d831c9979475f428051868ed0df65e5069

Observation 36c11f08-37e7-42c7-ae59-f38cec9c8fe8 · outbound

This paper cites Linevul: A transformer-based line-level vulner- ability prediction.

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection Linevul: A transformer-based line-level vulner- ability prediction

Reference 7

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raw_fallback, observed 2026-08-07T14:09:07.674937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:09:01.704620Z digest=sha256:d2a51e4fa583eb4a8d0a8530a574e859e5db9c716005d1fa24bb992a40930425

Observation be94fd98-fe0f-4a57-907a-0b6fc8cabccb · outbound

This paper cites Binaiv: Semantic-enhanced vulnerability detection for linux x86 binaries.

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection Binaiv: Semantic-enhanced vulnerability detection for linux x86 binaries

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:09:01.784748Z digest=sha256:3786ab8e0f66e5d56f1b953fdb38f91a16a4e9054293ddb44e814d5e0a2fa5f3

Observation 2bd7db58-b990-4ae2-95fa-b141af86558a · outbound

This paper cites DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence.

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:09:01.864943Z digest=sha256:be3bad69241a8425636852ebbd2d24b5f001def8288fe200b6455c401b771546

Observation 5a9ab519-fe7b-4498-9651-f58b8a834c94 · outbound

This paper cites Outside the comfort zone: Analysing llm capabilities in software vulnerability detection.

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection Outside the comfort zone: Analysing llm capabilities in software vulnerability detection

Reference 10

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raw_fallback, observed 2026-08-07T14:09:07.074839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:09:01.960237Z digest=sha256:aa24bb691f3ee5075f5ca1937579215e3f810eb1504a181388516ee578af74ac

Observation 08f52629-b115-4262-a17b-41d1b2701d98 · outbound

This paper cites Large language models for code: Security hardening and adversarial testing.

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection Large language models for code: Security hardening and adversarial testing

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:09:02.015105Z digest=sha256:62bf44dbf7fc5e129e83576d3838905e94c3ae3f6cac6ca71e4befc153957c59

Observation 13daf1a2-e200-4387-8905-19c2ee26de1f · outbound

This paper cites Linevd: Statement-level vulnerability detection using graph neural networks.

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection Linevd: Statement-level vulnerability detection using graph neural networks

Reference 12

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raw_fallback, observed 2026-08-07T14:09:06.674774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:09:02.093488Z digest=sha256:048e2cc6fc381ad88a2d98cc7560bf6330881464343b412ca80679eb61302e12

Observation 3f6f2760-a18a-4590-9520-18a7ebaee44d · outbound

This paper cites Qwen2.5-Coder Technical Report.

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection Qwen2.5-Coder Technical Report

Reference 13

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no resolver link, observed 2026-08-07T14:09:02.194848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:09:02.194848Z digest=sha256:abff0f8fb5ea7d66548c1f794c55ac75278f48df50ace9b20b5028a3028e3177

Observation 6549ba68-065e-4805-aa9a-176e45492013 · outbound

This paper cites LLM-Assisted Code Cleaning For Training Accurate Code Generators.

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection LLM-Assisted Code Cleaning For Training Accurate Code Generators

Reference 14

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no resolver link, observed 2026-08-07T14:09:02.284613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:09:02.284613Z digest=sha256:53b95977ae0b35e0d6ff88648bc3b08b0feeb68a5cfd3b144f7e4422f60c0d85

Observation 7f89d785-a6b7-4ef9-bc34-8760e80d1d64 · outbound

This paper cites Mistral 7B.

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection Mistral 7B

Reference 15

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no resolver link, observed 2026-08-07T14:09:02.368873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:09:02.368873Z digest=sha256:94c616e0aa8fd2387c0a72aebd09841640b61348e4b4553e1406521ea54e6f46

Observation a4eb7679-4220-49fe-bab5-e904417d0a04 · outbound

This paper cites More Agents Is All You Need.

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection More Agents Is All You Need

Reference 16

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no resolver link, observed 2026-08-07T14:09:02.474889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:09:02.474889Z digest=sha256:e36b9dfdb9890d0b7e47c6dc6e8027b812c7bf6a7098fa0a98b59c138a397aca

Observation ab700f1e-27a7-4a03-9450-28d18178a287 · outbound

This paper cites Vulnerability management in linux distributions: An empirical study on debian and fedora.

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection Vulnerability management in linux distributions: An empirical study on debian and fedora

Reference 17

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raw_fallback, observed 2026-08-07T14:09:06.335487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:09:02.563821Z digest=sha256:4d677e2d779723c88be8ff06d92e46ef8f5f14bbd74a836d001444eb33bd63d2

Observation 2a66c58d-653c-4790-8777-522b90363c26 · outbound

This paper cites Megavul: Ac/c++ vulnerability dataset with comprehensive code representations.

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection Megavul: Ac/c++ vulnerability dataset with comprehensive code representations

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:09:02.614753Z digest=sha256:728b71184e062e3d3e57239bb8b50e092202a55ce33a327e8253460ac25e2498

Observation b4a8d715-be84-4840-93d7-b4371af59214 · outbound

This paper cites Top Score on the Wrong Exam: On Benchmarking in Machine Learning for Vulnerability Detection.

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection Top Score on the Wrong Exam: On Benchmarking in Machine Learning for Vulnerability Detection

Reference 19

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:09:02.715563Z digest=sha256:ce1d4b5d8c449a5362842a0e5ee2a6b066e74d9cf4c01149870b3176f78453a1

Observation c5a5f61a-649d-4a01-81ba-c324576356b9 · outbound

This paper cites LProtector: An LLM-driven Vulnerability Detection System.

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection LProtector: An LLM-driven Vulnerability Detection System

Reference 20

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:09:02.793299Z digest=sha256:41179c974b789ac94b49375300e68af5e55835dee0de992d38b6d45a63a22386

Observation 4e542395-0863-46cf-ab38-0d69c41d9554 · outbound

This paper cites A systematic literature review on automated software vulnerability detection using machine learning.

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection A systematic literature review on automated software vulnerability detection using machine learning

Reference 21

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raw_fallback, observed 2026-08-07T14:09:05.849365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:09:02.875131Z digest=sha256:543dcb0a1a22377437275732e27355afa232334b54a4c0f758c7ebdd75ff20c0

Observation 112e7eb0-bc16-4d0e-b88b-440d12f733bc · outbound

This paper cites Simulating strategic reasoning: Comparing the ability of single llms and multi-agent systems to replicate human behavior.

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection Simulating strategic reasoning: Comparing the ability of single llms and multi-agent systems to replicate human behavior

Reference 22

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raw_fallback, observed 2026-08-07T14:09:05.551887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:09:02.994750Z digest=sha256:f660c2618aece297f493cb399ce204aff4f8f511fea8993ae0ee44a61954eaab

Observation 7b150650-86db-44b3-831b-6489232f5ae6 · outbound

This paper cites Multi-Agent Collaboration Mechanisms: A Survey of LLMs.

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection Multi-Agent Collaboration Mechanisms: A Survey of LLMs

Reference 23

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:09:03.185290Z digest=sha256:eae3b0fc1dcf3ecf92a05b56576227255497e8706ed095bd76b5e65d4960e696

Observation 5cd071fa-e9dc-4e35-ae9f-8de37f454c38 · outbound

This paper cites Large language model for vulnerability detection: Emerging results and future directions.

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection Large language model for vulnerability detection: Emerging results and future directions

Reference 24

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raw_fallback, observed 2026-08-07T14:09:05.054750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:09:03.264826Z digest=sha256:1a2c78970b4e8c3cebd66b9dfbb44e905de5fac2bc497b91c5048f4bc7e212f8

Observation 2fdf72a3-35f0-4c4c-82d7-c9b29e4a4767 · outbound

This paper cites relevant context.

SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection relevant context

Reference 25

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raw_fallback, observed 2026-08-07T14:09:04.774749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T14:09:03.342895Z digest=sha256:b73bb305875969a2b19d19908380598d718ad170b725d645f061172f49a7b8c5

Pith citing papers

Observation 3335d6c9-997a-4a55-abf1-39b619b0fd84 · inbound

VulnRepairEval: An Exploit-Based Evaluation Framework for Assessing Large Language Model Vulnerability Repair Capabilities cites this paper.

VulnRepairEval: An Exploit-Based Evaluation Framework for Assessing Large Language Model Vulnerability Repair Capabilities SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection

Reference 3

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T11:02:54.227103Z digest=sha256:d2aa547b1fe822440bcce171abfff92435b3a9ed1e288dddb1f5b8da582ce021

Observation d50d42f2-d11b-4ea7-a370-ba0edb90fc77 · inbound

VULPO: Context-Aware Vulnerability Detection via On-Policy LLM Optimization cites this paper.

VULPO: Context-Aware Vulnerability Detection via On-Policy LLM Optimization SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection

Reference 24

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no resolver link, observed 2026-08-03T22:12:31.417987Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T22:12:31.417987Z digest=sha256:9f8a9f2cc2d40d2745ebce1119fceb92257bb999a195b3f9935ac6a0dc18f6d7

Observation 2bb33fad-bcb2-44c6-abc3-d32b463dfadd · inbound

ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage cites this paper.

ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection

Reference 2

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arxiv_id, observed 2026-05-22T09:41:21.777646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-22T09:40:21.746161Z digest=sha256:573862476aba627559297c177edb34cec8defaf2c065d63ed0763060631c98f2

Observation edaebdec-b228-4a68-ad2f-a58ad29127ba · inbound

Needles at Scale: LLM-Assisted Target Selection for Windows Vulnerability Research cites this paper.

Needles at Scale: LLM-Assisted Target Selection for Windows Vulnerability Research SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection

Reference 1

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arxiv_id, observed 2026-07-01T21:36:14.802704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-28T16:48:15.968088Z digest=sha256:da3a97409c82837a37b2d9da2d5d9996ed342bc0f27468e4843fbe04bfdc809c

Observation 72810641-d066-46c2-893a-5cf1c42f3274 · inbound

Multi-Source Cybersecurity Logs: An ATT&CK-Labeled Dataset and SLM Evaluation cites this paper.

Multi-Source Cybersecurity Logs: An ATT&CK-Labeled Dataset and SLM Evaluation SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection

Reference 24

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arxiv_id, observed 2026-07-03T21:58:59.103098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-26T23:56:34.841978Z digest=sha256:50fcd2f3489f06059b242f08bc1b787c72ccfba0616524e595d9b37cebbf6a62

Observation 07613a3b-58b9-479a-b8a6-5a7d806cb29e · inbound

Evaluating LLMs for Real-World Web Vulnerability Detection cites this paper.

Evaluating LLMs for Real-World Web Vulnerability Detection SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection

Reference 1

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arxiv_id, observed 2026-07-04T07:09:37.549787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-26T13:50:13.974457Z digest=sha256:f638cf9d692808abe7fd11cf139405868149784a187d6f95b7dbe77c80b13738

Observation 01bef7ce-6348-48a5-90fb-c49ec924f19b · inbound

Neuro-Symbolic Reasoning for Vulnerability Detection cites this paper.

Neuro-Symbolic Reasoning for Vulnerability Detection SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection

Reference 2

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no resolver link, observed 2026-07-11T22:42:57.965190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T22:42:57.965190Z digest=sha256:c058b15d0e52dc059ec57d7c8e5ec7d2e06ba0523b2eb4b1f2aea8ab5e983e65

Observation a38550a7-ed79-44c2-b4fb-c585beeb62e6 · inbound

DREA: Decoupled Reasoning and Exploration Agents for Repository-Level Vulnerability Detection cites this paper.

DREA: Decoupled Reasoning and Exploration Agents for Repository-Level Vulnerability Detection SecVulEval: Benchmarking LLMs for Real-World C/C++ Vulnerability Detection

Reference 1

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no resolver link, observed 2026-08-02T05:13:49.632959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:13:49.632959Z digest=sha256:c486bf495f90cd8c76211003291023fe3ef8f3a5e4bade95f505cd0f2c448dea