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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 12 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 2026-08-12T06:34:41.77262+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:f158c351cf791778aa5a2d97c6596fbaf4d4b1c76f51b025e69c0e7f248dbed6

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:fc2508fbec14ff30b233f503879bb82d655f194909309f7c2e102ab8e3daaf7c

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:ee5ed2451204e6c2125cc487bdcf1a809cbcc597eb7be7cd5c4391bcde0a171e

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=sha256:88e631f9168645a0354a38ae92ce271e5dfbcdba42c772125a7b68b8e99b3ae9

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=sha256:0c27ca4e4166e1b5210b772e78b3394492600032882b6aef33bf24744aca75ff

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:da1cd31e5ba59e7bc6a27da344b749de194dc1790b48b664f2e8620ba5ea5dd4

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=sha256:4ede3be71e17e37031b931f210bd52f0e12f27c4c32bd07b32f3ed3f306839a1

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=sha256:329b6a79cf8d2933302cb41155e0e1916bc6779ceb991951e8cbf69bc66851b3

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=sha256:208695bb16764cc83fbedf7e636870e5cc68e055686933e3ecbfb5d893b44e6c

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:bbbe900af07a1587c30e5adb995a2819c9db20e8b50296abe93cc984459c54af

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=sha256:1ff035b9fe42ef9bf6e700d6149c26b60484e01ced7c37ab1b2eda63198d1117

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=sha256:79e177d830108158283a3ce915091fb8c63a072f91eeff2db805eac07c869d00

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:d03535bf68878e60b4aa254d1aa219b89aa9086b0e799833bd3b4e78f0ba11cc

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=sha256:2ce84d4d17f4bd0928104b6d571799a4a8be2f8f126283715aacd76befc9a05a

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=sha256:42d0c0403de1e445fe8561a5fc894f6da2bb6dcea514427b16aea31ae368ed77

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:f967fb18c660c113f7cc268d0d996316784c6f20a7920e15663fad4dfbc0e9e6

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=sha256:38a8ec3496e3f4b62412c13ba3951ac724f5c74990512443c79daa5398510296

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=sha256:2ffb1ca8483d7bdbb91f702f94f4b4c4f96529a478ca6c3fd3f74a69f71b1de7

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=sha256:382bbd66ebbd32b9841b177e79897179dd8bc4c50d767cf0454220ce449486c1

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=sha256:28d3b94453dc91d108e49f7e908590b42032605605ff31d286ea853710a48957

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:bb3d5eef1ea9d438478f3fb65abc6eae4614b5acfd74ef8ac931ef495d7048b3

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=sha256:662e8870071ad9cb18b865e2b219f9570645b9fa95650ac4e8ebd58f37c86109

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:f013dad5233473611dfaafd5bf4f854ac238089b84b83196618d6e21e050960c

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:e5aebe42e6097e373c59fd8bcd7c9ffced8582987f722160785fceaa53819c5b

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:c52ab0c99a9e9b61903edfd1bc81af291b0d0a0240c8c637f584913ffd990ad2

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=sha256:8b93621abc67f7f2f9f8260b3fc316129225977f2c0cd84ce9d39abfe80706b2

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:c611ee33d6c6cf35c7f4b27940eba872281384332e228f92909c4ec872dc9f51

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=sha256:941041c5c604bbe08e70d7a773e7b371d85127eb059f2010e63c98151b839bbd

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=sha256:684668c18201dfbe054889000714abd0e3a40ce2703eff098bcb5bbe60b115f3

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=sha256:3113e25dac68f3ae8ba60289fe42bac68666e49e171360914c2fc2e7f09da747

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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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:d038a12648065638b931e82e9b7e9c6734363823bf916f7cd4985495eb538691

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:a1481aa87224235400180483b1ef0313539a25882781816b37ba491ec8095025

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=sha256:4f30502939131e6eb7d8fdbaff36746921363002e42bfb859171c035f817b87b

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=sha256:9d3d6e0ca7f357fe90dafbc24eb26c0bff1e031cb5c3c3cda4ffde02fb2b87c4

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:c5f0bf2ec3f529172bb60dc5f1723ce3903852f68350b983681294f82039f0fe

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=sha256:05fa6fbadb7bfe53649452d14e35d0e2981ed1fd124b9bf880db5f8f648024b0

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-reported events for the cited work

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source=pdf_text observed=2026-08-04T19:25:52.663774Z digest=sha256:751d436ed9b51300b59460183e4bf7116ef2815b2bcfd5d3acd9280abba588e0

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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no resolver link, observed 2026-08-04T19:25:52.668613Z

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source=pdf_text observed=2026-08-04T19:25:52.668613Z digest=sha256:4c88bd3c04cbdf112bc86d2230368d122f2875ae6371ceef9858717456a6b396

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

Source-reported events for the cited work

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source=pdf_text observed=2026-08-04T19:25:52.672884Z digest=sha256:541028b034df187c395ebdcf8f046ddaae9d0b82b1d9992e7dafef0145c746df

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

Source-reported events for the cited work

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source=pdf_text observed=2026-08-04T19:25:52.677591Z digest=sha256:3b3faa1eab27cb90d18303b13f4a3a4e1c634ea7a71f0b6043b3a86f2b0bf630

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

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source=pdf_text observed=2026-08-04T19:25:52.681797Z digest=sha256:8257241c0dff72eda9537379f6e74b17ab5303ad2397bfb93ed2ad4729cf8a72

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-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T19:25:52.686093Z digest=sha256:d460410441fcb780e85d33cb2add4d819950659caa0f1de5ce66727f716ccb22

Pith citing papers

No inbound Pith citation observations are available.