Paper Citation Record · LEDGER

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing

As of 20 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2508.14300.

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

pith.paper-citation-record.v1
2508.14300 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T18:42:13.543655Z

measured 40 of 40 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 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

40 of 40 outbound references displayed

verified exact0
verified fuzzy0
unresolved40
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c12aa628-5183-4780-8335-93916e9c037e · outbound

This paper cites Sutton, A.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Sutton, A

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:09.282529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d68cf2c1-a1bc-47e2-8fef-d5eb1988e307 · outbound

This paper cites A Survey of Network Protocol Fuzzing: Model, Techniques and Directions.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing A Survey of Network Protocol Fuzzing: Model, Techniques and Directions

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:09.406917Z

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Observation 22c61b59-2501-4b78-8914-20cd12894ba2 · outbound

This paper cites A survey of automatic protocol reverse engineering tools,.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing A survey of automatic protocol reverse engineering tools,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:09.537209Z

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Unavailable: canonical work link unavailable.

Observation e1f1471f-b3c7-410d-860e-c50da8718ac2 · outbound

This paper cites State selection algorithms and their impact on the performance of stateful network protocol fuzzing,.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing State selection algorithms and their impact on the performance of stateful network protocol fuzzing,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:09.690059Z

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Unavailable: canonical work link unavailable.

Observation c97cb5c1-8245-4df2-b515-7280a5575336 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Evaluating Large Language Models Trained on Code

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:09.849740Z

Source-reported events for the cited work

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Observation afbf040a-034f-43dc-87fc-2120faec41aa · outbound

This paper cites Language models can solve computer tasks,.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Language models can solve computer tasks,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:09.992731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64510e11-2ef7-412b-8906-e985a84be4bc · outbound

This paper cites On the Challenges of Fuzzing Techniques via Large Language Models.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing On the Challenges of Fuzzing Techniques via Large Language Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:10.173990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b4a331f-2b90-49ff-bbca-8792ffeb9e3a · outbound

This paper cites Generative ai and large language models for cyber security: All insights you need,.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Generative ai and large language models for cyber security: All insights you need,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:10.314136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 669eb343-bf14-4b5a-8fd0-62e0b26c91e3 · outbound

This paper cites Large language model guided protocol fuzzing,.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Large language model guided protocol fuzzing,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:10.471650Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70145940-3fff-4d0d-85a1-8bf8791c4b6c · outbound

This paper cites Dense x retrieval: What retrieval granularity should we use?.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Dense x retrieval: What retrieval granularity should we use?

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:10.622172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ae1f2aa-7be6-4ff1-91a1-328d5521596f · outbound

This paper cites Retrieval- augmented generation for knowledge-intensive nlp tasks,.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Retrieval- augmented generation for knowledge-intensive nlp tasks,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:10.729192Z

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Unavailable: canonical work link unavailable.

Observation 31a11d87-afab-4c0c-b2d9-1d0215d26882 · outbound

This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing ReAct: Synergizing Reasoning and Acting in Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:10.896986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c84f377-9d8f-4682-a003-b88d84826266 · outbound

This paper cites The art, science, and engineering of fuzzing: A survey,.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing The art, science, and engineering of fuzzing: A survey,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:11.034298Z

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Observation 7b78f274-e6c5-4f18-a47d-689ebe851f64 · outbound

This paper cites A survey on the development of network protocol fuzzing techniques,.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing A survey on the development of network protocol fuzzing techniques,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:11.175669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e97b1d7-138f-47e7-8ef3-314f8d290817 · outbound

This paper cites Attention is all you need,.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Attention is all you need,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:11.270116Z

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Unavailable: canonical work link unavailable.

Observation ba052825-935c-4e57-bfd4-fa9f79d0bcb9 · outbound

This paper cites Chatphishdetector: Detecting phishing sites using large language models,.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Chatphishdetector: Detecting phishing sites using large language models,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:11.337302Z

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Unavailable: canonical work link unavailable.

Observation 4d7f24b4-5def-45a8-b907-80f3d0ec9f6e · outbound

This paper cites Retrieval Augmented Generation Based LLM Evaluation For Protocol State Machine Inference With Chain-of-Thought Reasoning.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Retrieval Augmented Generation Based LLM Evaluation For Protocol State Machine Inference With Chain-of-Thought Reasoning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:11.447745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4044dc3-8391-497c-9417-e173bbc7e8e4 · outbound

This paper cites Harnessing Large Language Models for Seed Generation in Greybox Fuzzing.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Harnessing Large Language Models for Seed Generation in Greybox Fuzzing

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:11.568038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b2017f0-722f-40b5-bc0a-86f28c0a0871 · outbound

This paper cites Codamosa: Escaping coverage plateaus in test generation with pre-trained large language models,.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Codamosa: Escaping coverage plateaus in test generation with pre-trained large language models,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:11.686673Z

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Observation 2cb87c3f-dc18-4bf6-9476-51e6dcf77a08 · outbound

This paper cites Erpa: Efficient rpa model integrating ocr and llms for intelligent document processing,.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Erpa: Efficient rpa model integrating ocr and llms for intelligent document processing,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:11.800171Z

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Observation 41c7e164-f7a2-47eb-9884-45b0759e0662 · outbound

This paper cites LMRPA: Large Language Model-Driven Efficient Robotic Process Automation for OCR.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing LMRPA: Large Language Model-Driven Efficient Robotic Process Automation for OCR

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:11.915790Z

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Unavailable: canonical work link unavailable.

Observation 0ddfe8ea-13b7-4fdc-a448-11fb1f47f4b7 · outbound

This paper cites LMV-RPA: Large Model Voting-based Robotic Process Automation.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing LMV-RPA: Large Model Voting-based Robotic Process Automation

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:12.015119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a46f44a4-5b76-42a3-9d75-c03a06a01802 · outbound

This paper cites LLM Multi-Agent Systems: Challenges and Open Problems.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing LLM Multi-Agent Systems: Challenges and Open Problems

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:12.137601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 812fc49e-2059-403b-8262-6ca2f1969d3c · outbound

This paper cites PentestAgent: Incorporating LLM Agents to Automated Penetration Testing.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing PentestAgent: Incorporating LLM Agents to Automated Penetration Testing

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:12.239014Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 587242c3-4473-4ecb-a827-38e7f9426b8d · outbound

This paper cites Ics protocol fuzzing: Coverage guided packet crack and generation,.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Ics protocol fuzzing: Coverage guided packet crack and generation,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:12.328806Z

Source-reported events for the cited work

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Observation 0447eb4c-3653-42c3-8ddc-0272bf267409 · outbound

This paper cites Bbuzz: A bit-aware fuzzing framework for network protocol systematic reverse engineering and analysis,.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Bbuzz: A bit-aware fuzzing framework for network protocol systematic reverse engineering and analysis,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:12.487409Z

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Unavailable: canonical work link unavailable.

Observation 6de7e853-340a-4057-baae-76710f3ee4c2 · outbound

This paper cites Pulsar: Stateful black-box fuzzing of proprietary network protocols,.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Pulsar: Stateful black-box fuzzing of proprietary network protocols,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:12.590791Z

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Unavailable: canonical work link unavailable.

Observation 4da59bc1-451d-44fd-91e0-2238803fea05 · outbound

This paper cites American fuzzy lop,.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing American fuzzy lop,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:12.684208Z

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Unavailable: canonical work link unavailable.

Observation ee306f5d-1197-4e79-b419-435c84b11411 · outbound

This paper cites {AFL++}: Combin- ing incremental steps of fuzzing research,.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing {AFL++}: Combin- ing incremental steps of fuzzing research,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:12.709627Z

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Unavailable: canonical work link unavailable.

Observation 30f84266-4d9b-4596-a3ca-8b1f6eaa8087 · outbound

This paper cites Aflnet: a greybox fuzzer for network protocols,.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Aflnet: a greybox fuzzer for network protocols,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:12.758511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b47414c-0cab-49b9-9776-b42ec55daa74 · outbound

This paper cites Nsfuzz: Towards efficient and state-aware network service fuzzing,.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Nsfuzz: Towards efficient and state-aware network service fuzzing,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:12.848094Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04e5c484-2795-4274-a0bd-a2e1dd29652f · outbound

This paper cites Augmenting Greybox Fuzzing with Generative AI.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Augmenting Greybox Fuzzing with Generative AI

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:12.932098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b365281-a909-4fac-94ff-3102ea7109a7 · outbound

This paper cites Msfuzz: Augmenting protocol fuzzing with message syntax comprehension via large language models.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Msfuzz: Augmenting protocol fuzzing with message syntax comprehension via large language models

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:12.995219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 72f89634-60f1-4178-97f7-45fd3df52a18 · outbound

This paper cites Large language models are zero-shot fuzzers: Fuzzing deep-learning libraries via large language models,.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Large language models are zero-shot fuzzers: Fuzzing deep-learning libraries via large language models,

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:13.075885Z

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Unavailable: canonical work link unavailable.

Observation a75f46c9-6726-4c54-899e-3c059964828b · outbound

This paper cites Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:13.131228Z

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Unavailable: canonical work link unavailable.

Observation 539dbd65-fb69-45a5-8c32-351ea5981922 · outbound

This paper cites NVD - Home,.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing NVD - Home,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:13.223935Z

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Unavailable: canonical work link unavailable.

Observation 00cd4577-cac5-4ab8-b690-06ef0ec58f0c · outbound

This paper cites LangChain,.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing LangChain,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:13.313160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 287a97a6-b51f-4dd6-b16a-61590a2ba824 · outbound

This paper cites an unresolved cited work.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Unresolved cited work

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:13.378414Z

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Unavailable: canonical work link unavailable.

Observation d9e052d7-cbc4-44d4-ab5b-612bf9378841 · outbound

This paper cites Groq is Fast AI Inference,.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Groq is Fast AI Inference,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:13.454719Z

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Unavailable: canonical work link unavailable.

Observation b6ea51bf-9a9a-4bbf-ba50-4eff9f95e60e · outbound

This paper cites Profuzzbench: A benchmark for stateful protocol fuzzing,.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Profuzzbench: A benchmark for stateful protocol fuzzing,

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:13.543655Z

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Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.