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Paper Citation Record · LEDGER

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation

As of 7 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2507.12084.

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

pith.paper-citation-record.v1
2507.12084 v1

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:01:21.638787Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

51 of 51 outbound references displayed

  • verified exact0
  • verified fuzzy50
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2b85f9b3-7808-4b0b-a735-649949011ea4 · outbound

This paper cites An overview on smart contracts: Challenges, advances and platforms,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation An overview on smart contracts: Challenges, advances and platforms,

Reference 1

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:17.774018Z digest=sha256:3097336b7670ad5c877c780d86a2294b23e917d2faa2afc8a0d0bf4b02d57d0e

Observation c2a6fca2-6832-47db-8c62-112e19815be3 · outbound

This paper cites Blockchain smart contracts: Applications, challenges, and future trends,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Blockchain smart contracts: Applications, challenges, and future trends,

Reference 2

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raw_fallback, observed 2026-08-06T17:01:30.470696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:17.848763Z digest=sha256:86d2e09be0ea0fb5d38fe554d8cb4bd4c2adbe940235382e7f595bd6022deadb

Observation d171444b-5dec-4800-b1f9-ae1b8c7be2cc · outbound

This paper cites Challenges and common solutions in smart contract development,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Challenges and common solutions in smart contract development,

Reference 3

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raw_fallback, observed 2026-08-06T17:01:30.285986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:17.965858Z digest=sha256:cfc6de1b780923e03420d46cec45a2b45e6dca33e3af2b7902aee21ac80c03b3

Observation 67da1848-6edf-4c2e-95dd-dcae03666062 · outbound

This paper cites A survey on smart contract vulnerabilities: Data sources, detection and repair,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation A survey on smart contract vulnerabilities: Data sources, detection and repair,

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:18.082278Z digest=sha256:c96935ef60ff29843f2572d0ab371aab05e63d28e3d396a9032d59027ba20363

Observation da991df7-382e-4c9d-92a1-3eab7fb20a65 · outbound

This paper cites Understanding a revolutionary and flawed grand experiment in blockchain: the dao attack,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Understanding a revolutionary and flawed grand experiment in blockchain: the dao attack,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:18.187024Z digest=sha256:8e3e69b9fc77ca9f4fc5c3729490180561e82139608e504544d750d6da128c28

Observation 64761143-2812-4bd3-8ef5-608b496c741c · outbound

This paper cites Vulnerability detection techniques for smart contracts: A systematic literature review,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Vulnerability detection techniques for smart contracts: A systematic literature review,

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:18.271568Z digest=sha256:a5faaf49b0d0c906152dccf124bcc1926b308e991206c6da4eb201d9d87929d8

Observation 2057b1a9-65fb-4330-ad19-e4e4c22fa7b0 · outbound

This paper cites Fuzzing: a survey,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Fuzzing: a survey,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:18.355669Z digest=sha256:1d45bd73e29332e505a9874ebc69f961ba45eaf2da54c73ced212642bb7bdd4f

Observation efc28dcf-1f7e-4cba-9430-843a9f059b01 · outbound

This paper cites Adversarial generation method for smart contract fuzz testing seeds guided by chain- based llm,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Adversarial generation method for smart contract fuzz testing seeds guided by chain- based llm,

Reference 8

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T17:01:18.441362Z digest=sha256:09e36684a3c597288fe8b42ece19ab4b2fee497c7658c12608fede4cbcb37fde

Observation 79429211-1fa3-4d75-9688-3c7eccaa1160 · outbound

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

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Codamosa: Escaping coverage plateaus in test generation with pre-trained large language models,

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:18.546897Z digest=sha256:627c1f83db3dd3f5587c44edcc1eb177e1353f45d5ab95e9e241fc86c97c8e87

Observation 60dce541-5daa-468a-9567-b37c54b43a0b · outbound

This paper cites Combining Fine-Tuning and LLM-based Agents for Intuitive Smart Contract Auditing with Justifications.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Combining Fine-Tuning and LLM-based Agents for Intuitive Smart Contract Auditing with Justifications

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:01:18.609117Z digest=sha256:3c08ab81822c5ddc7ebb88f549662a24a6a8504eb784438d97d859a05752d082

Observation 7a0e1e54-e260-4665-9401-a032e8697924 · outbound

This paper cites Large language model guided protocol fuzzing,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Large language model guided protocol fuzzing,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:18.705336Z digest=sha256:06523fe7e4ff0fb60057b403c0d546c89349e404a4805eb3001fb0eeea5b9aaf

Observation d5f98c1b-dedd-4f17-a3a5-821a548cde06 · outbound

This paper cites Fuzz4all: Universal fuzzing with large language models,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Fuzz4all: Universal fuzzing with large language models,

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:18.785036Z digest=sha256:5d04a4bfbc0b150d24375ed83d37a3129065f6aec31f44ce65c0701dd9b6568f

Observation 5156056c-a122-48f0-a9a3-5a5f40b8872d · outbound

This paper cites MuFuzz: sequence- aware mutation and seed mask guidance for blockchain smart contract fuzzing,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation MuFuzz: sequence- aware mutation and seed mask guidance for blockchain smart contract fuzzing,

Reference 13

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:18.868983Z digest=sha256:8fbd99635a9f323b5b49fc6b94c04aaded1cbd7eb846fddf5794ff7bb0b0b5fc

Observation 23442b64-64c5-46dc-bcc1-2afb5fc821fa · outbound

This paper cites Fuzzing: a survey for roadmap,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Fuzzing: a survey for roadmap,

Reference 14

Resolution
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:18.955336Z digest=sha256:38a293d353180770413b9bd12554b96e56f1b017c00a1eb82b1867e39b0738a3

Observation 62aba4e1-ff9f-43de-aa25-182a59e15099 · outbound

This paper cites Are we there yet? unraveling the state-of-the-art smart contract fuzzers,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Are we there yet? unraveling the state-of-the-art smart contract fuzzers,

Reference 15

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:19.010679Z digest=sha256:0c10a538cb50a11eb783502c303efe849ba98ba0b30f64e94efc0b967a271e89

Observation 2d674819-f86d-4ef9-9cc6-048d9aabb3db · outbound

This paper cites Seed selection for successful fuzzing,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Seed selection for successful fuzzing,

Reference 16

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source=pdf_text observed=2026-08-06T17:01:19.098384Z digest=sha256:6ca0cbcf0105fc8c0d9f8bc27a88c843f8f55e04bbabf9fd854b3fff76b5f277

Observation 26fb28b2-ae08-4e40-9cad-d67a79a09daf · outbound

This paper cites Testing smart contracts gets smarter,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Testing smart contracts gets smarter,

Reference 17

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:19.172632Z digest=sha256:eb52337de36535ccafa94c0642e8e936ad9edceabd878d7c27fa4cebac81cdab

Observation 3bd42afd-7c05-457f-aafe-e4b6bed11f59 · outbound

This paper cites sfuzz: An efficient adaptive fuzzer for solidity smart contracts,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation sfuzz: An efficient adaptive fuzzer for solidity smart contracts,

Reference 18

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:19.238127Z digest=sha256:ea9158df01e9cc53b4269a89eae5f7e6a7c52bbe1134b841fceac2ef8a108ed6

Observation 67573e3a-6379-444e-a957-8318f0f52eea · outbound

This paper cites Smartian: Enhancing smart contract fuzzing with static and dynamic data-flow analyses,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Smartian: Enhancing smart contract fuzzing with static and dynamic data-flow analyses,

Reference 19

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:19.319610Z digest=sha256:58648270458726d081c40e0f94a3e7e6d669430bf74dfa4c30184593a564c3ba

Observation 001d0398-7c82-4f3b-bd5b-3737f340a054 · outbound

This paper cites Increasing fuzz testing coverage for smart contracts with dynamic taint analysis,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Increasing fuzz testing coverage for smart contracts with dynamic taint analysis,

Reference 20

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:19.380495Z digest=sha256:4b4ace0de90903a90e27bdbf1f48282da3598287ace00ddca05f356f2e7134c3

Observation e7cca2e7-1c83-4428-be8d-4f0c2fb3c982 · outbound

This paper cites Securify: Practical security analysis of smart contracts,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Securify: Practical security analysis of smart contracts,

Reference 21

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:19.456334Z digest=sha256:7052e5c7836e6ab10bfe2d2082e8f9ccda57959b71887d507438cbca69068092

Observation c5cd8807-9716-4d68-87e4-3e472ebf3866 · outbound

This paper cites Smartcheck: Static analysis of ethereum smart contracts,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Smartcheck: Static analysis of ethereum smart contracts,

Reference 22

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raw_fallback, observed 2026-08-06T17:01:27.184494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:19.545904Z digest=sha256:98ceef48836883106d56a40af2526a47f5a6d778bec1764f451d783fa700a207

Observation ac219054-432f-4fbf-ac0b-b8eb38afbe09 · outbound

This paper cites Contractward: Automated vulnerability detection models for ethereum smart contracts,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Contractward: Automated vulnerability detection models for ethereum smart contracts,

Reference 23

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:19.612405Z digest=sha256:a6dbebd935a060fe15e8f35c9383b2a1922992ee73a1bc484d552c74695c5826

Observation 2c682034-0650-4474-84c3-16131c98c4cd · outbound

This paper cites Manticore: A user-friendly symbolic execution framework for binaries and smart contracts,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Manticore: A user-friendly symbolic execution framework for binaries and smart contracts,

Reference 24

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raw_fallback, observed 2026-08-06T17:01:26.869091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:19.692481Z digest=sha256:5e34c39a977bdefbb6bf78bbdc828a65b3e5116fa0a543c6c98ac90ecfc6223e

Observation 51e3019c-90bd-479e-99c6-c40ed3b18cb6 · outbound

This paper cites Zeus: analyzing safety of smart contracts.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Zeus: analyzing safety of smart contracts

Reference 25

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raw_fallback, observed 2026-08-06T17:01:26.733718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:19.798468Z digest=sha256:143c0f9cf692a8efb2754478274fa4515b12a0e7e9ed0796ffdcd2da676b238d

Observation 739db11b-e3f0-4aee-8d5b-51b4350d1225 · outbound

This paper cites Slither: a static analysis framework for smart contracts,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Slither: a static analysis framework for smart contracts,

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:19.884347Z digest=sha256:9b3d3a01231d11bdd81df8e27da98e3147bce37e114492e971128069b194f5e4

Observation 3d8b418f-268b-49eb-8d14-9de8901956f9 · outbound

This paper cites Ityfuzz: Snapshot-based fuzzer for smart contract,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Ityfuzz: Snapshot-based fuzzer for smart contract,

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:19.959391Z digest=sha256:c995055b8443a365a5bdedad14acea9739a9c71c326ad09318213c0a5c1c16f5

Observation 6bd82595-edb5-4ade-adf4-f6a2b456c77a · outbound

This paper cites Reguard: finding reentrancy bugs in smart contracts,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Reguard: finding reentrancy bugs in smart contracts,

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:20.059740Z digest=sha256:9c799dc641c666a015b5d87910853d2f8342bfb12a27d9b864a3404f0b09798e

Observation aeacf922-ba69-465e-a938-8072c820fd59 · outbound

This paper cites xfuzz: Machine learning guided cross-contract fuzzing,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation xfuzz: Machine learning guided cross-contract fuzzing,

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:20.136599Z digest=sha256:6a762b086c32516a9ba681324d4f91ff5c32f60cb84a6fd4db26cf2b04817f3f

Observation 6ec89fd8-6f85-4f1d-87a9-569238ba76b4 · outbound

This paper cites A systematic literature review of blockchain and smart contract development: Tech- niques, tools, and open challenges,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation A systematic literature review of blockchain and smart contract development: Tech- niques, tools, and open challenges,

Reference 30

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raw_fallback, observed 2026-08-06T17:01:25.805840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:20.201593Z digest=sha256:a9fa2699336a6863844fb2157b667f367517938da631cb31e631cb24be1bf38e

Observation 87243b84-2fab-40bf-b62f-0c0035b6021d · outbound

This paper cites Learning to fuzz from symbolic execution with application to smart contracts,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Learning to fuzz from symbolic execution with application to smart contracts,

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:20.282906Z digest=sha256:2aeb7663ab026e4b21edb24538cb6b77a194ece777cff67b3364153303df5cfd

Observation 05285897-1071-4efb-bf33-aa29caf7ebe1 · outbound

This paper cites Confuzzius: A data dependency-aware hybrid fuzzer for smart contracts,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Confuzzius: A data dependency-aware hybrid fuzzer for smart contracts,

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:20.365409Z digest=sha256:17bc0a3b5592ce95028a14abc04c8e97a68feb9fced795b1a3f0528e68ad768a

Observation 9704a51d-da5c-4ba6-bf2e-c7f564f0f14a · outbound

This paper cites Effectively generating vulnerable transaction sequences in smart contracts with reinforcement learning-guided fuzzing,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Effectively generating vulnerable transaction sequences in smart contracts with reinforcement learning-guided fuzzing,

Reference 33

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raw_fallback, observed 2026-08-06T17:01:25.271994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:20.447495Z digest=sha256:6b9e79f4c6d05469229c5596c19d1c7022c153b51e12861e289604eb3aa041ef

Observation 5528c1d0-c70a-4bc3-a9ba-bc5b269605d3 · outbound

This paper cites Verismart: A highly precise safety verifier for ethereum smart contracts,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Verismart: A highly precise safety verifier for ethereum smart contracts,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:01:25.144494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:20.531332Z digest=sha256:7085610fff7f5f2384817b48de928454d10bc4cbbfb659ce920bd70a8d5e0e32

Observation 6dba9597-b4a8-4fc9-a608-13fdd76d6af8 · outbound

This paper cites Smart contract vulnerability detection using graph neural networks,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Smart contract vulnerability detection using graph neural networks,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:01:24.920710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:20.599440Z digest=sha256:6cada2dce9da53d236557b4e7146ce3cf36c26a44d10293accd0666e1eacc9ae

Observation ee2cddbb-6e04-44c8-844d-2c45846630ac · outbound

This paper cites Empirical review of automated analysis tools on 47,587 ethereum smart contracts,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Empirical review of automated analysis tools on 47,587 ethereum smart contracts,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:01:24.718902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:20.654555Z digest=sha256:1cf41497503374a1198bab89ac22903dc4b425197565763b993705a9abe496a2

Observation 334b472b-4823-4220-bf4e-7797936b583f · outbound

This paper cites Swc registry,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Swc registry,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:01:24.565411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:20.710340Z digest=sha256:93fd9566f764bae3ad9c813deda19462b0f34c3beb3649e5d1e2ee64a24247a8

Observation 875cc2d6-05fc-425a-b5c9-72fcb2b284dd · outbound

This paper cites Finding the greedy, prodigal, and suicidal contracts at scale,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Finding the greedy, prodigal, and suicidal contracts at scale,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:01:24.368752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:20.795228Z digest=sha256:e026bc4ef1489e28884d27d3d6558b600d07b6cb0b88f0c06f969f798cbb9936

Observation 6e75e8d1-69f8-4f97-a690-78b537b6ae7f · outbound

This paper cites Defectchecker: Automated smart contract defect detection by analyzing evm bytecode,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Defectchecker: Automated smart contract defect detection by analyzing evm bytecode,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:01:24.126654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:20.868163Z digest=sha256:73f404cd6247e8ef57ad892d908cf41c88264bdbc93433866fd0ef1d5dd6339f

Observation 14cbfc47-6598-4810-85e7-e422b03158e1 · outbound

This paper cites Mythril: A security analysis tool for evm bytecode,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Mythril: A security analysis tool for evm bytecode,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:01:23.953424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:20.925639Z digest=sha256:dfbcc65b4136af93917a2105f7c32961b68f5785a4e0d30d17d75a9cd4943d22

Observation 1983ec98-2060-4680-9544-3eb96982ab74 · outbound

This paper cites Osiris: Hunting for integer bugs in ethereum smart contracts,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Osiris: Hunting for integer bugs in ethereum smart contracts,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:01:23.746664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:21.011237Z digest=sha256:105aacdd5aba9360ee3b64b5d1a25d9e898522548315024b9f8fb6f1e965f42d

Observation cd12f402-2091-4b64-bb59-daa28c1a9f6a · outbound

This paper cites Making smart contracts smarter,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Making smart contracts smarter,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:01:23.556415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:21.102666Z digest=sha256:bf8d7d63c7677b1a34bcfff82aefa534a9710230b41eda461854e657477d721e

Observation 5390981a-3e8c-419d-a580-4e2ae7193191 · outbound

This paper cites teEther: Gnawing at ethereum to automatically exploit smart contracts,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation teEther: Gnawing at ethereum to automatically exploit smart contracts,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:01:23.379036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:21.147446Z digest=sha256:1bea2b9299051edf8e2fcd333001b27cccfc5dd5763d35b5c75a0fe9f06ff7de

Observation a575c89d-6ca8-476e-85e6-5206a4e12d56 · outbound

This paper cites Contractfuzzer: Fuzzing smart contracts for vulnerability detection,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Contractfuzzer: Fuzzing smart contracts for vulnerability detection,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:01:23.247416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:21.209896Z digest=sha256:76f9514376ec712b3d10ad0ecf4c83008e07c3f7550b6a8a3f3aea4ac7d7e929

Observation 1c4a571f-f77e-4ef4-853b-1c99afcd0139 · outbound

This paper cites Oracle-supported dynamic exploit generation for smart contracts,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Oracle-supported dynamic exploit generation for smart contracts,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:01:23.088164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:21.260131Z digest=sha256:aba2357366f7f93780e8554208ef296c63c6626c4e98d3884f5f125a0e93362a

Observation 6d3cf223-023a-40d9-b7f0-7fd15de7df85 · outbound

This paper cites Echidna: effective, usable, and fast fuzzing for smart contracts,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Echidna: effective, usable, and fast fuzzing for smart contracts,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:01:22.883410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:21.331057Z digest=sha256:c4bf3b1adccd13c93c7adc712f27d0b063a9c28b4e4b6e68604a8f267dfcce94

Observation 22850875-727d-4794-b89b-d17469e18bc3 · outbound

This paper cites Harvey: A greybox fuzzer for smart contracts,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Harvey: A greybox fuzzer for smart contracts,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:01:22.700227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:21.397772Z digest=sha256:30f4681d4089283914d9748460b542e2f65050b769bbd9366300d4bc324cabb7

Observation 61a4dd89-37f9-42e1-b203-5077ee6796af · outbound

This paper cites Rethinking smart contract fuzzing: Fuzzing with invocation ordering and important branch revisiting,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Rethinking smart contract fuzzing: Fuzzing with invocation ordering and important branch revisiting,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:01:22.519847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:21.461701Z digest=sha256:854da0f7a9d229342d4b508c1368e1b7c46bcfb58a96a2d52d04d12d10c8d0f6

Observation 73575c64-13c8-4ed3-97aa-5afa5708e6e5 · outbound

This paper cites Smartgift: Learning to generate practical inputs for testing smart contracts,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Smartgift: Learning to generate practical inputs for testing smart contracts,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:01:22.329001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:21.513917Z digest=sha256:abd047d28c65f0a01bc4e2a93889fe6d6dd7175fe48ad9e9ff23fba698083630

Observation 022f1117-b5cb-4f8a-b5d8-b64850cff135 · outbound

This paper cites Soliaudit: Smart contract vulnerability assessment based on machine learning and fuzz testing,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Soliaudit: Smart contract vulnerability assessment based on machine learning and fuzz testing,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:01:22.095509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:21.572511Z digest=sha256:f67c11ddb922c75fc9999bff41ad405fda10001f638cac28eb11aacf54d6d369

Observation 43def1be-7fc4-4843-88ac-217bf7d153ef · outbound

This paper cites Syntest-solidity: Automated test case generation and fuzzing for smart contracts,.

LLAMA: Multi-Feedback Smart Contract Fuzzing Framework with LLM-Guided Seed Generation Syntest-solidity: Automated test case generation and fuzzing for smart contracts,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:01:21.868920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T17:01:21.638787Z digest=sha256:9351c1b4fb714e17e08808a0aa56ead367ac7c6b745b05b8541783813a405107

Pith citing papers

No inbound Pith citation observations are available.