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Paper Citation Record · LEDGER

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection

As of 9 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2509.09291.

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

pith.paper-citation-record.v1
2509.09291 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T19:25:52.686093Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

43 of 43 outbound references displayed

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External citation measurements

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Outbound references

Observation c4120182-0710-492d-96ac-8291d574b565 · outbound

This paper cites Automatic fingerprinting of vulnerable BLE IoT devices with static UUIDs from mobile apps,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection Automatic fingerprinting of vulnerable BLE IoT devices with static UUIDs from mobile apps,

Reference 1

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source=pdf_text observed=2026-08-04T19:25:52.457257Z digest=sha256:4e537a72979371286e5c7aa97c3101c06f03e36bb2280b53db30eefa6c47395b

Observation 8318d800-5600-49be-8fff-1fad848fce8c · outbound

This paper cites BLESS: A BLE application security scanning framework,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection BLESS: A BLE application security scanning framework,

Reference 2

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source=pdf_text observed=2026-08-04T19:25:52.463720Z digest=sha256:317d8ccbe2b509ddb04766c20592be5cf7603f8187a75f50fb373abb40a9cdb1

Observation 96a18cbd-157a-414a-976e-57ba857003d9 · outbound

This paper cites BLESA: Spoofing attacks against reconnections in bluetooth low energy,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection BLESA: Spoofing attacks against reconnections in bluetooth low energy,

Reference 3

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source=pdf_text observed=2026-08-04T19:25:52.468704Z digest=sha256:fb49f671d17a3777c44ff39a18f7ee6b5c4a278410d8feadfaf46e6ee2578423

Observation bb3ae60c-cd3e-4508-a0bb-1f22afc2351b · outbound

This paper cites Breaking secure pairing of bluetooth low energy using downgrade attacks,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection Breaking secure pairing of bluetooth low energy using downgrade attacks,

Reference 4

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source=pdf_text observed=2026-08-04T19:25:52.474234Z digest=sha256:8f709bc2ccdf62da43f1bcdfd81fae7ab0427f6af1b228bfdaaf2a5a148e18a9

Observation 886f8697-fde8-4483-b6a6-dabbddc0bd06 · outbound

This paper cites FirmXRay: Detecting bluetooth link layer vulnerabilities from bare-metal firmware,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection FirmXRay: Detecting bluetooth link layer vulnerabilities from bare-metal firmware,

Reference 5

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source=pdf_text observed=2026-08-04T19:25:52.480466Z digest=sha256:70b679b0d481c48d8a541b054053db3b04a6b9eed12e1094dbac271045c2dd39

Observation 9b24f59e-71e0-4580-860b-6653b626c7ff · outbound

This paper cites Bluetooth core specification v5. 1,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection Bluetooth core specification v5. 1,

Reference 6

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source=pdf_text observed=2026-08-04T19:25:52.485273Z digest=sha256:8909952d841af842bbc362b658c3a79c775307fb0c8afc50b65fac8d71937b47

Observation 5eb33751-1dbb-4d36-9985-7c3893bb7d20 · outbound

This paper cites Attention is all you need,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection Attention is all you need,

Reference 7

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source=pdf_text observed=2026-08-04T19:25:52.490903Z digest=sha256:682ae04235d0f3a498ea472caed806ec4965e81fdde4fc899b30e1d8a66ec1a6

Observation 4b3d87e6-b035-4d1f-8a57-8b116ab4cfb5 · outbound

This paper cites If LLMs Would Just Look: Simple Line-by-line Checking Improves Vulnerability Localization.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection If LLMs Would Just Look: Simple Line-by-line Checking Improves Vulnerability Localization

Reference 8

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source=pdf_text observed=2026-08-04T19:25:52.495927Z digest=sha256:94687126243ca10a39a26a97c096e612e723e936bf3e3eff95be00ed55ab4fae

Observation f23e1685-8a67-433f-abd9-e19afb17ba1c · outbound

This paper cites A survey on large language model (LLM) security and privacy: The good, the bad, and the ugly,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection A survey on large language model (LLM) security and privacy: The good, the bad, and the ugly,

Reference 9

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source=pdf_text observed=2026-08-04T19:25:52.502176Z digest=sha256:266d9f5d0495df2bfb2fc612d4d0e37e4a2fc09d4796e61ff48f5b938029679c

Observation 6e0182fa-3224-4db7-8b28-aa73467a5b05 · outbound

This paper cites Llm- based test-driven interactive code generation: User study and empirical evaluation,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection Llm- based test-driven interactive code generation: User study and empirical evaluation,

Reference 10

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source=pdf_text observed=2026-08-04T19:25:52.506998Z digest=sha256:c6a9e69e13719030d13b4aad4238b7ec25cda5a5d5f90fdcebead4d2e17aed9a

Observation 54f24f52-14be-414f-b28f-0c711e939c19 · outbound

This paper cites An efficient cryptographic protocol verifier based on prolog rules,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection An efficient cryptographic protocol verifier based on prolog rules,

Reference 11

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source=pdf_text observed=2026-08-04T19:25:52.511931Z digest=sha256:0546daf1d0037716ea25970b73943bcf1ad0dab74d2c66b18bc130e352dee5ee

Observation 68dd644b-8600-4835-9354-a47ff4d4599b · outbound

This paper cites Multitask-based evaluation of open- source LLM on software vulnerability,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection Multitask-based evaluation of open- source LLM on software vulnerability,

Reference 12

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source=pdf_text observed=2026-08-04T19:25:52.516424Z digest=sha256:4cd9b7dc9f6008a0a59a89d72773dbf10314ed460504daef9f5dd718168cb388

Observation 84f05787-da1b-4643-b415-e4d5a805d04e · outbound

This paper cites To Err is Machine: Vulnerability Detection Challenges LLM Reasoning.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection To Err is Machine: Vulnerability Detection Challenges LLM Reasoning

Reference 13

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source=pdf_text observed=2026-08-04T19:25:52.524061Z digest=sha256:d3d8d41cec7d0d5df5e90e074dd61cdd62a019ee4b0f8c56c2e66627cb794d14

Observation 6df943cb-c42f-48f4-9c14-975a3c5973de · outbound

This paper cites Vulnerability detection with code language models: How far are we?.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection Vulnerability detection with code language models: How far are we?

Reference 14

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source=pdf_text observed=2026-08-04T19:25:52.531069Z digest=sha256:971737a8a9c48b732bbdfe9ac979fe2bb3996f8c22676ee2fd56d8c7e0c15af5

Observation 5bcef70e-3e69-430f-b53e-daf1799f5289 · outbound

This paper cites Androzoo: Collecting millions of android apps for the research community,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection Androzoo: Collecting millions of android apps for the research community,

Reference 15

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source=pdf_text observed=2026-08-04T19:25:52.537040Z digest=sha256:d7c0c9aec8c603405fb4b09d45b535b89a377b1b7ff41216d52851f1f6f75194

Observation 290450dd-c4f1-4ffb-b550-3ce0a6addba5 · outbound

This paper cites A study of the feasibility of co- located app attacks against BLE and a Large-Scale analysis of the current Application-Layer security landscape,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection A study of the feasibility of co- located app attacks against BLE and a Large-Scale analysis of the current Application-Layer security landscape,

Reference 16

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source=pdf_text observed=2026-08-04T19:25:52.541808Z digest=sha256:7855ce9aa735245c4c366f8bd1073a752d198cc9b2a79f2d38d9142bdb396522

Observation 117b0f94-742f-411d-bf1c-9f2f5e92bdfb · outbound

This paper cites SweynTooth: unleashing mayhem over bluetooth low energy,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection SweynTooth: unleashing mayhem over bluetooth low energy,

Reference 17

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source=pdf_text observed=2026-08-04T19:25:52.547083Z digest=sha256:214591eee3ddcbb20c198bd01584f6a68ec4932dddd6b980d5f790141b2e0a08

Observation 199c6d85-16ae-4f70-83f9-7e7c10bf03a0 · outbound

This paper cites Finding traceability attacks in the bluetooth low energy specification and its im- plementations,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection Finding traceability attacks in the bluetooth low energy specification and its im- plementations,

Reference 18

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source=pdf_text observed=2026-08-04T19:25:52.552263Z digest=sha256:fc879111e6c0a6be947694a3b17c2558ca3dd03a493ea315cbf076bd4518e9a8

Observation 8abf8edc-b9be-4fe1-b94d-a0d739183666 · outbound

This paper cites Extrapolating formal analysis to uncover attacks in bluetooth passkey entry pairing.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection Extrapolating formal analysis to uncover attacks in bluetooth passkey entry pairing

Reference 19

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source=pdf_text observed=2026-08-04T19:25:52.559592Z digest=sha256:043e5f89118924a39165f802b1245361d7adaa5db5113a6771edec9cbea9d58c

Observation 2ccafd6b-8624-4e74-a638-c05f751ea754 · outbound

This paper cites BlueSW AT: A lightweight state-aware security framework for bluetooth low energy,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection BlueSW AT: A lightweight state-aware security framework for bluetooth low energy,

Reference 20

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source=pdf_text observed=2026-08-04T19:25:52.565391Z digest=sha256:b7a118dfa8e123d6f97bc1b4c688be1592c4607546227d04577baa61d7504b9b

Observation bc57a07a-3f0f-42f9-bedc-56cddeabea8b · outbound

This paper cites Eddystone- eid: Secure and private infrastructural protocol for ble beacons,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection Eddystone- eid: Secure and private infrastructural protocol for ble beacons,

Reference 21

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source=pdf_text observed=2026-08-04T19:25:52.571159Z digest=sha256:5ecafc7cf1827958841c75fdb98382b34d1f2ccfa699de9851f4186f22db8439

Observation fb080a56-5e9b-4593-8b56-f1dae7bf53de · outbound

This paper cites MiniBLE: Exploring insecure BLE API usages in mini-programs,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection MiniBLE: Exploring insecure BLE API usages in mini-programs,

Reference 22

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source=pdf_text observed=2026-08-04T19:25:52.577161Z digest=sha256:1193f2b548c48c2284c2b53c6ccd0757a35029d5b77aa190eb0bf663c17176ee

Observation 05d45fb7-d9d9-4857-a671-4106d7d3bb6e · outbound

This paper cites Vul-RAG: Enhancing LLM-based vulnerability detection via knowledge-level RAG,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection Vul-RAG: Enhancing LLM-based vulnerability detection via knowledge-level RAG,

Reference 23

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source=pdf_text observed=2026-08-04T19:25:52.582400Z digest=sha256:cbf46a73eb4f79cabf8820f7d0b27a83189f8f02418a10fbda319fc38677dc9b

Observation a95a7975-1992-4db7-8413-5318869550b5 · outbound

This paper cites On hardware security bug code fixes by prompting large language models,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection On hardware security bug code fixes by prompting large language models,

Reference 24

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source=pdf_text observed=2026-08-04T19:25:52.589003Z digest=sha256:eeea3c16c27bf1fc9fd87da7446c2526ca2bb0c0d622c36083a7223cf8f5387c

Observation 98820469-28cc-416b-ba2f-8eb104ef2059 · outbound

This paper cites Transformer-based language models for software vulnera- bility detection,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection Transformer-based language models for software vulnera- bility detection,

Reference 25

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source=pdf_text observed=2026-08-04T19:25:52.594296Z digest=sha256:94ffe5411306e498ca182e77885e43215e9072e169ae3a252c7425de4ac7681c

Observation 2aa75e9c-02a4-4557-bdb9-ff6780cfa5c4 · outbound

This paper cites Software vul- nerability detection using large language models,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection Software vul- nerability detection using large language models,

Reference 26

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source=pdf_text observed=2026-08-04T19:25:52.600031Z digest=sha256:5b44231c9d248e20d9db6ea7eefd8c502ed095271d97e82830bcad137069a4a2

Observation 4d98dbeb-7e96-4337-8b47-eff40b6ce4d1 · outbound

This paper cites DrAttack: Prompt decomposition and reconstruction makes powerful LLMs jailbreakers,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection DrAttack: Prompt decomposition and reconstruction makes powerful LLMs jailbreakers,

Reference 27

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source=pdf_text observed=2026-08-04T19:25:52.604730Z digest=sha256:8c3839c6159f24108dcf24f39b0d7abc017e283bbe1ed996e97b6a66f56ac988

Observation f32d4043-e7f0-4355-8943-f07a0a2df8fb · outbound

This paper cites COLD-attack: Jailbreaking LLMs with stealthiness and controllability,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection COLD-attack: Jailbreaking LLMs with stealthiness and controllability,

Reference 28

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source=pdf_text observed=2026-08-04T19:25:52.609245Z digest=sha256:c4dc9da385f10d81443c84098d1d774e9ae480b5f86c845efff9fe6fb16a9901

Observation 57a90d98-905b-422e-af2e-3e29d6647873 · outbound

This paper cites DeepInception: Hypnotize large language model to be jailbreaker,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection DeepInception: Hypnotize large language model to be jailbreaker,

Reference 29

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source=pdf_text observed=2026-08-04T19:25:52.615025Z digest=sha256:7d614f17abcca031af1425c8affdf4b5ec8c48985467f0028b5706c022b13102

Observation e250a2a3-b243-4b35-8981-9abf74f066f6 · outbound

This paper cites Can large language models provide security & privacy advice? measuring the ability of llms to refute misconceptions,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection Can large language models provide security & privacy advice? measuring the ability of llms to refute misconceptions,

Reference 30

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source=pdf_text observed=2026-08-04T19:25:52.619804Z digest=sha256:043ad4f22db330f5aaad225cf98323cc41c58e9b4a68139f2c8bfb3ae875a04c

Observation bd46c3cc-7f5b-43a4-bff9-ae916fb05e43 · outbound

This paper cites Examining zero-shot vulnerability repair with large language models,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection Examining zero-shot vulnerability repair with large language models,

Reference 31

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source=pdf_text observed=2026-08-04T19:25:52.624672Z digest=sha256:54720d66923c580254a0352034101a0696b5d5fdd8d5ee26fd5e36880a563c1e

Observation 373a6e38-f342-43d2-9606-195e5ae26a56 · outbound

This paper cites On protecting the data privacy of large language models (LLMs) and LLM agents: A literature review,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection On protecting the data privacy of large language models (LLMs) and LLM agents: A literature review,

Reference 32

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source=pdf_text observed=2026-08-04T19:25:52.629253Z digest=sha256:b11f0694cc1f4b91517a304eb6ab11d25034fd02b7d1216485d9f139443ff425

Observation 086910a0-0916-4bb2-abd6-74e85e514e33 · outbound

This paper cites LLM-guided formal verification coupled with mutation testing,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection LLM-guided formal verification coupled with mutation testing,

Reference 33

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source=pdf_text observed=2026-08-04T19:25:52.635109Z digest=sha256:740af350ad3fc75043d952462396f6319947eb72854110392541b687ee90a76e

Observation 6b199154-fcfd-4294-854d-3e01943c00f5 · outbound

This paper cites SecureFalcon: Are we there yet in automated software vulnerability detection with LLMs?.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection SecureFalcon: Are we there yet in automated software vulnerability detection with LLMs?

Reference 34

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source=pdf_text observed=2026-08-04T19:25:52.639824Z digest=sha256:b8d4f5b9e5c3fa830a54cf097bb1f5363c6d6a369e9442e124b2704f66777a5e

Observation 8c0045ce-d124-4136-b3d3-c50d7abf8c98 · outbound

This paper cites Effectiveness of large language models to generate formally verified C code,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection Effectiveness of large language models to generate formally verified C code,

Reference 35

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source=pdf_text observed=2026-08-04T19:25:52.649000Z digest=sha256:cfd53319025772d593d80f030d5d374e3d04346ccc6df1882957d6de5a3519df

Observation 75017214-bdaa-483b-a705-8edcbe10eae6 · outbound

This paper cites Domain- adapted LLMs for VLSI design and verification: A case study on formal verification,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection Domain- adapted LLMs for VLSI design and verification: A case study on formal verification,

Reference 36

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source=pdf_text observed=2026-08-04T19:25:52.654073Z digest=sha256:deadaf960714823232a6e1be0a683fe446bdc42e6e6f1e4d06309aa733b540c1

Observation a4e95339-6073-46d2-affe-ada1c8bb6a71 · outbound

This paper cites Generative AI augmented induction-based formal verification,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection Generative AI augmented induction-based formal verification,

Reference 37

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no resolver link, observed 2026-08-04T19:25:52.659063Z

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source=pdf_text observed=2026-08-04T19:25:52.659063Z digest=sha256:0dfad2ffe9431adfdcac885ae64d2b905aa32c59a8830769d94070582ba626f0

Observation ea23dd1c-61af-492e-9786-b58650e20ec3 · outbound

This paper cites (Security) assertions by large language models,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection (Security) assertions by large language models,

Reference 38

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source=pdf_text observed=2026-08-04T19:25:52.663774Z digest=sha256:a51b28d39bd8960cff62a131848cad77f86f434127980a6684f28c2dff9e1fd0

Observation fe53e082-26a4-48a4-b19b-3ec2c3f13591 · outbound

This paper cites Don’t trust: Verify-grounding LLM quantitative reasoning with autoformalization,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection Don’t trust: Verify-grounding LLM quantitative reasoning with autoformalization,

Reference 39

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source=pdf_text observed=2026-08-04T19:25:52.668613Z digest=sha256:ae9d171a4c17b2bb9744cfab50a055f91f067ecb9f6c6e6265982146736f8bb4

Observation f1a8193c-5e3b-40b3-83db-17b528187155 · outbound

This paper cites VeriPlan: Integrating formal verification and LLMs into end-user planning,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection VeriPlan: Integrating formal verification and LLMs into end-user planning,

Reference 40

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no resolver link, observed 2026-08-04T19:25:52.672884Z

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source=pdf_text observed=2026-08-04T19:25:52.672884Z digest=sha256:3bb03edcba51946e5771ab7e479e9bd97975d4a6e3f17fcd35b57c48ed1b639e

Observation f0382076-1f89-4f7a-b192-df0362bd8c00 · outbound

This paper cites Formal-LLM: Integrating formal language and natural language for controllable LLM- based agents,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection Formal-LLM: Integrating formal language and natural language for controllable LLM- based agents,

Reference 41

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no resolver link, observed 2026-08-04T19:25:52.677591Z

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source=pdf_text observed=2026-08-04T19:25:52.677591Z digest=sha256:4805c2bb4a1ddca301fa96caab940daffece9ee97537c80c4f3d1e359adc26e5

Observation 7be0b5d8-f23b-4ce1-aef8-536a8999c021 · outbound

This paper cites FVEL: Interactive formal verification environment with large language models via theorem proving,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection FVEL: Interactive formal verification environment with large language models via theorem proving,

Reference 42

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no resolver link, observed 2026-08-04T19:25:52.681797Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-04T19:25:52.681797Z digest=sha256:a6901f3ac3ad9b14bfbe5ebb5958b7abaf229af250c9485fc6857236e13848ac

Observation 28842885-112d-4e50-9b49-29dac31d6427 · outbound

This paper cites CryptoFormalEval: Integrating large language models and formal verification for automated crypto- graphic protocol vulnerability detection,.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection CryptoFormalEval: Integrating large language models and formal verification for automated crypto- graphic protocol vulnerability detection,

Reference 43

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source=pdf_text observed=2026-08-04T19:25:52.686093Z digest=sha256:948542e901e0fd034cf96dea1df5edcc166eeb34d1f5d861d962b4d2e44f4928

Pith citing papers

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