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Paper Citation Record · LEDGER

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

As of 10 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 2026-08-09T06:31:02.800959+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

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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raw_fallback, observed 2026-08-06T17:01:30.705815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:17.774018Z digest=sha256:e4d272af52b41692ec84980e3f9d646f923e0f49b347644d11ac82e83678d5d5

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:17.848763Z digest=sha256:5199685a8c8333ca778f6d0313c3618abc1d309312135b8ff9785e1e302d3172

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:17.965858Z digest=sha256:aeb4d4e05ac6e8d6c0d83a22349c0db4bf3135cf6f0b2bc72fe44be58945c975

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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raw_fallback, observed 2026-08-06T17:01:30.089973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:18.082278Z digest=sha256:6acc878d6bcb20554d7d5d894651eb53350e5a4135957cf5400ba01eea82b989

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:18.187024Z digest=sha256:b290e1bbce122c585f2cd58a32ced2ded8b58471025c3afb5c5805923ea5f035

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:18.271568Z digest=sha256:64dc797fd029b0be6a809d169c92713f3f02de9baaa55874de2c8dd3c4312a33

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:18.355669Z digest=sha256:b86f2392685f86804e7f790b5f4415dddcd7a9828b5e93118195649e4706d4cb

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

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:18.441362Z digest=sha256:d93de87ffbb8fe2e0ddd573c6d073768b01ee5f8be3325e48e254ea5c3008126

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:18.546897Z digest=sha256:0f006d438691beb483b7f91db0642f74d72c9e9268d4724634feef343c1111c7

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=sha256:94b0d080f67d8a823f6ac45da005918a9d391147988de65ba6e9869fce1bbc29

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:18.705336Z digest=sha256:3345f86aef30fc7c78beb2a3aa1121d69136631028c15b342bd713d084e91561

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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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:18.785036Z digest=sha256:5d0883d48fb96b333c9502810d40d83b79a1699e8a378456bee2024f79796ea9

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:18.868983Z digest=sha256:01abe43bee5140838a814f48a3bbbe15e84507eaa4c46fe08c7e8008fe0efc1b

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

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:18.955336Z digest=sha256:ac99e91a9d2d9b2db2f61c8f89453911de15bf16005baf95a9023854ea809f2b

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:19.010679Z digest=sha256:60a9b3dba386a2ca05d297700ac1dd0e3f487befa0f8091e4ae9a47bc19b0469

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:f9a5585098f49f93a3f9a75989c372ab3ee4963b26824883d5f85624877ae5c9

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:19.172632Z digest=sha256:aa4b13ad7b29f790eb8e9226fe99241891d491b50ac98bbfa5842dab14009226

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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source=pdf_text observed=2026-08-06T17:01:19.238127Z digest=sha256:d313ce936199d30a86173df41f7e177ebfa6bdfdb446ec1e47190b05fcb4661c

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:19.319610Z digest=sha256:49099464343bf02e491f81d59bcfc9c2d190327353a5a2ada6c50584ce1f73c6

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:19.380495Z digest=sha256:d96a22fdb0450d77db263797b43265bd791e3dc405036d46fbbb8d914b888ace

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:19.456334Z digest=sha256:f54ec14dfcc39f92e4f8475164990fc6dae4c49a6d0bc8a7203a60970461b388

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:19.545904Z digest=sha256:c1ad08c9a76c22562455f663794f3b22ec9e01bc58e4ad3c71bea040988df1f6

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:19.612405Z digest=sha256:96941c3f2134321a62adfac134ae3630ba19ae27176d1a67c7b2cbaac5ffae03

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

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:19.692481Z digest=sha256:88db7707affc4ac38f43ed95dd9c679ec6b46475189e87422cb9550d328cf9d6

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:19.798468Z digest=sha256:b2d7c49904c10b41dd19862979ca34be0a8ccf244b814ea0777fd6e43e412ce6

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:19.884347Z digest=sha256:0a88f85294838fa0a10c818eef33afb542f3bb4afb3efeff691cf4e873957c8d

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:19.959391Z digest=sha256:39985525245b27b30f7b02c953c0208e470bb66bbe7d4c2062e94d91bf133aec

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:20.059740Z digest=sha256:b88c00b9bae7aa8c066518f69b0892bef5b924e1640c678746c558a251c2a872

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:20.136599Z digest=sha256:a0f8d2712fcd3c5c3f64a8b6e7cb2ea0bd65659e981447c1b6418bd2c249b546

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:20.201593Z digest=sha256:8e95992170d6c10cab318e24c1a34ac1829aebffbef5f521f69c1c77a84d7ad0

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:20.282906Z digest=sha256:5c976e146cde7bae8168d4f1228326b7e7c08b2f85d8307f52f3d3247e8f8e54

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:20.365409Z digest=sha256:f4d97b9d67d74987c1f11c97f1cf680079fac0f9b87a7ddfdc2dc55a4d063ec3

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:20.447495Z digest=sha256:4837f13d171870e5cfbe2bb961b166a359f83870a222660ba6125be71be57c80

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:20.531332Z digest=sha256:d8888f2dad07ed37f8b1c1dfe12875411fde8004101919aa55277a0e980653f9

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:20.599440Z digest=sha256:0d1e512eeb504ca8444ba51f7bdfbb491eb216258fe4e1cc92b2a542277ea8a9

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:20.654555Z digest=sha256:fa9b485184f73d9295978559a7c95238a5c7340e3b08b015d0f9d4268b387beb

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:20.710340Z digest=sha256:47957e42ff62a75614aaaeff3246cc58243393605e81802891059e863e2080b3

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:20.795228Z digest=sha256:656f091e84ffc2fa91dbd5b4d5355adefddd0e78ea3da0d05407ca03a95ae7db

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:20.868163Z digest=sha256:bc49ec07163bb815b5685d4e522d6b7ad9b6e74e141ccf5b1f7d80fe7f5c4c3a

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:20.925639Z digest=sha256:7526996044107918e38f96a58707d1a58ea8a72b5ecb5fede2bb292fa62f5404

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:21.011237Z digest=sha256:833f5962cae8298d4fe1b9c4e7dc228e53c52145714ca8d48021695a7eb512c3

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:21.102666Z digest=sha256:cb35456c7cc5bb9d86f49d06c8cbfcd48127bf506f061ef0f66a53a17e48c94a

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:21.147446Z digest=sha256:746a6db149817829f751790033d000ef19589a4feb42dca842d7e8d0ed538747

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:21.209896Z digest=sha256:829633718e7061a61115a32487fdf6e0bd29de9d6a160f112f15156925cdbd3f

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:21.260131Z digest=sha256:a0e0d104779b13406199df0778be28aed93e65792a0036f3cf7d48852796f08f

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:21.331057Z digest=sha256:31d3f60bf06de4772e6a717bd198e8be5ed57bd70a5b09742e456c325f530212

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:21.397772Z digest=sha256:ec966db0cfb1483a4466a4a7099612647230a692e5f5910d784a37c2ae065bf7

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:21.461701Z digest=sha256:d8e6f2ac7dfc6beed1b34d4cf5500f3121f88541afad96a0cb73e40b1b01a8b6

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:21.513917Z digest=sha256:8387434858d56f3da5b4f33dbc42926ebaf1b5efb841963d540a672d78545280

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:21.572511Z digest=sha256:2274c62ed93493d293d5c0c1fcfef0201206bdf4cf38112319a04068e9f99a12

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:01:21.638787Z digest=sha256:0b1e9c11050822c4f7cceb220deb64c97cce87b4404be8b65f0884fc700fd59a

Pith citing papers

No inbound Pith citation observations are available.