SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection | Paper Citation Record

Observation 874c2d01-cc50-40a9-bfff-65715f5d9251 · outbound

This paper cites Swan, Blockchain: Blueprint for a new economy.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Swan, Blockchain: Blueprint for a new economy

Reference 1

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Observation b743ebc2-d705-46bf-af18-50791ac9ecc4 · outbound

This paper cites Survey on blockchain based smart contracts: Applications, opportunities and challenges,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Survey on blockchain based smart contracts: Applications, opportunities and challenges,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.859782Z

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Observation 50945950-7f45-4625-80c2-9315ae63034a · outbound

This paper cites Ethereum: A secure decentralised generalised trans- action ledger,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Ethereum: A secure decentralised generalised trans- action ledger,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.845308Z

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Observation 879e70a6-71b6-46d8-8aae-96f4c73e53b2 · outbound

This paper cites Who are the money launderers? money laundering detection on blockchain via mutual learning-based graph neural network,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Who are the money launderers? money laundering detection on blockchain via mutual learning-based graph neural network,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.830703Z

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Observation 62222098-186f-4a55-9e95-4f489f833e75 · outbound

This paper cites Dccgraph: Detecting criminal communities with augmented criminal network construction and graph neural network,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Dccgraph: Detecting criminal communities with augmented criminal network construction and graph neural network,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.814720Z

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Observation 75795106-f0c6-4daf-98d0-adceb45c265e · outbound

This paper cites Topology augmented multi-band and multi-scale filtering for graph anomaly detection,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Topology augmented multi-band and multi-scale filtering for graph anomaly detection,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.799679Z

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Observation a2c0d33f-015b-4ba2-8cc0-2d49072b0154 · outbound

This paper cites Smart contract development: Challenges and opportunities,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Smart contract development: Challenges and opportunities,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.782247Z

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Observation b946c76a-f1c3-4e5c-b177-b8615733c171 · outbound

This paper cites The dao hacked,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection The dao hacked,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.766758Z

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Observation 066e0552-b464-444a-a48e-d7333763ee15 · outbound

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

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Understanding a revo- lutionary and flawed grand experiment in blockchain: the dao attack,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.751102Z

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Observation b933c29d-a1a7-4fdf-adb1-ad640edbba7a · outbound

This paper cites Smart-LLaMA: Two-Stage Post-Training of Large Language Models for Smart Contract Vulnerability Detection and Explanation.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Smart-LLaMA: Two-Stage Post-Training of Large Language Models for Smart Contract Vulnerability Detection and Explanation

Reference 10

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Observation 5f425e2a-9100-4ee4-ab09-d0b6c6fa753d · outbound

This paper cites Smart-llama-dpo: Reinforced large language model for explainable smart contract vulnerability detection,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Smart-llama-dpo: Reinforced large language model for explainable smart contract vulnerability detection,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.734809Z

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Observation 495b6715-a691-47e1-b18d-233b1eca05bb · outbound

This paper cites MOS: Towards Effective Smart Contract Vulnerability Detection through Mixture-of-Experts Tuning of Large Language Models.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection MOS: Towards Effective Smart Contract Vulnerability Detection through Mixture-of-Experts Tuning of Large Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T11:52:40.741387Z

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Observation 518bd7cb-0dab-41fd-91d1-e9bb9bb10db0 · outbound

This paper cites Blockchain-based Smart Contracts: A Systematic Mapping Study.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Blockchain-based Smart Contracts: A Systematic Mapping Study

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T11:52:40.746154Z

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Observation b5dfcda0-7b39-4968-a2ff-618a986e6bf4 · outbound

This paper cites Towards analyzing the complexity landscape of solidity based ethereum smart contracts,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Towards analyzing the complexity landscape of solidity based ethereum smart contracts,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.717473Z

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Observation 6a1e0f26-83d7-488a-a058-ccf4ec0d07bb · outbound

This paper cites Making smart contracts smarter,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Making smart contracts smarter,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.703376Z

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Observation 01254fec-cb39-4bd5-ae60-7387db4e3973 · outbound

This paper cites Mythril-reversing and bug hunting framework for the ethereum blockchain,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Mythril-reversing and bug hunting framework for the ethereum blockchain,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.687715Z

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Observation b651168c-64b8-4b2f-bfb0-80852451f22e · outbound

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

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Osiris: Hunting for integer bugs in ethereum smart contracts,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.673222Z

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Observation 2f0e896f-d603-4446-bd7d-92d4339d5885 · outbound

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

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Manticore: A user-friendly symbolic execution framework for binaries and smart contracts,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.658566Z

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Observation 52396d9f-419a-46fb-85ad-3c36d1586f2b · outbound

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

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Slither: a static analysis framework for smart contracts,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.643848Z

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Observation 776b41e4-1098-4be6-8602-7c8d1d36629c · outbound

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

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Smartcheck: Static analysis of ethereum smart contracts,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.629099Z

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Observation 31f5cc7c-57b6-4a5f-84a1-f3edf7c95c57 · outbound

This paper cites Improving smart contract security with contrastive learning-based vulnerability detection,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Improving smart contract security with contrastive learning-based vulnerability detection,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.612566Z

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Observation 8a5b650c-d3a0-4e3e-bd6f-66ce8a202124 · outbound

This paper cites Smart contract vulnerability detection using graph neural network.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Smart contract vulnerability detection using graph neural network

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.597154Z

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Observation 0e0a0093-3428-4404-82ce-0c1c8f87fa58 · outbound

This paper cites Scvhunter: Smart contract vulnerability detection based on heteroge- neous graph attention network,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Scvhunter: Smart contract vulnerability detection based on heteroge- neous graph attention network,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.578957Z

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Observation 84adbba9-dd9c-4603-8f02-655a2736e703 · outbound

This paper cites Peculiar: Smart contract vulnerability detection based on crucial data flow graph and pre-training techniques,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Peculiar: Smart contract vulnerability detection based on crucial data flow graph and pre-training techniques,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.562275Z

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Observation 82affd6a-cd32-4e9c-a3d3-52d03f7ab2ad · outbound

This paper cites Pscvfinder: A prompt-tuning based framework for smart contract vulnerability detection,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Pscvfinder: A prompt-tuning based framework for smart contract vulnerability detection,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.546724Z

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Observation 534f2daa-35eb-43f5-a5ef-78975e7c9a56 · outbound

This paper cites Codet5: Identifier-aware unified pre-trained encoder-decoder models for code understanding and generation,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Codet5: Identifier-aware unified pre-trained encoder-decoder models for code understanding and generation,

Reference 26

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Observation 40d32cf0-c1bf-47bf-ac4f-86bf894bb8c0 · outbound

This paper cites Graphcodebert: Pre-training code representations with data flow,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Graphcodebert: Pre-training code representations with data flow,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.515983Z

Source-reported events for the cited work

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Observation cc0cd8b8-b71c-47e7-81de-543a053a1b06 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Exploring the limits of transfer learning with a unified text-to-text transformer,

Reference 28

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Observation 0d9bf999-65a2-4f68-9f71-f02cd71bd41a · outbound

This paper cites Smartbugs: A framework to analyze solidity smart contracts,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Smartbugs: A framework to analyze solidity smart contracts,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.490816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f4fced67-d30e-4f9c-bf5f-95b2869591c4 · outbound

This paper cites Smart Contract Vulnerability Detection: From Pure Neural Network to Interpretable Graph Feature and Expert Pattern Fusion.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Smart Contract Vulnerability Detection: From Pure Neural Network to Interpretable Graph Feature and Expert Pattern Fusion

Reference 30

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Observation 99ce85d2-fd14-4abf-9824-04325b40fccc · outbound

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

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Rethinking smart contract fuzzing: Fuzzing with invocation ordering and important branch revisiting,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.475397Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 24245a53-a0cd-48e1-89cd-7f309470c340 · outbound

This paper cites Cross-modality mutual learning for enhancing smart contract vulnerability detection on bytecode,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Cross-modality mutual learning for enhancing smart contract vulnerability detection on bytecode,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.459899Z

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Observation 731fda6b-2466-4978-885d-4bd8818904ae · outbound

This paper cites Sael: Leveraging large language models with adaptive mixture-of-experts for smart contract vulnerability detection,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Sael: Leveraging large language models with adaptive mixture-of-experts for smart contract vulnerability detection,

Reference 33

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Observation 85bc7cea-4785-490d-875a-3200032b8dc0 · outbound

This paper cites A survey on ethereum sys- tems security: Vulnerabilities, attacks, and defenses,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection A survey on ethereum sys- tems security: Vulnerabilities, attacks, and defenses,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.426856Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f78a657f-c01a-42f6-a9a0-08c33e71b7df · outbound

This paper cites Easyflow: Keep ethereum away from overflow,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Easyflow: Keep ethereum away from overflow,

Reference 35

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0cc353be-27b3-4224-9fd6-e594d6c9e85c · outbound

This paper cites Security Analysis Methods on Ethereum Smart Contract Vulnerabilities: A Survey.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Security Analysis Methods on Ethereum Smart Contract Vulnerabilities: A Survey

Reference 36

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Observation 94db8525-58c9-4faa-9dcf-ec27660da2c6 · outbound

This paper cites Large Language Model-Powered Smart Contract Vulnerability Detection: New Perspectives.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Large Language Model-Powered Smart Contract Vulnerability Detection: New Perspectives

Reference 37

Resolution: verified exact; local_arxiv, observed 2026-08-06T11:52:41.068511Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e217daf7-5b9e-4ab5-82b3-1ccad90dfec5 · outbound

This paper cites When ChatGPT Meets Smart Contract Vulnerability Detection: How Far Are We?.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection When ChatGPT Meets Smart Contract Vulnerability Detection: How Far Are We?

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T11:52:40.870385Z

Source-reported events for the cited work

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Observation 60988f3a-ff9a-4f94-b1b9-1e8d918d4f17 · outbound

This paper cites Do you still need a manual smart contract audit?.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Do you still need a manual smart contract audit?

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-06T11:52:40.875375Z

Source-reported events for the cited work

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Observation 3dd9c061-0fd2-48c8-9d72-7570f6c317d5 · outbound

This paper cites Gptscan: Detecting logic vulnerabilities in smart contracts by combining gpt with program analysis,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Gptscan: Detecting logic vulnerabilities in smart contracts by combining gpt with program analysis,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.392881Z

Source-reported events for the cited work

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Observation afb47c32-e52e-4851-85ae-b338a406b49e · outbound

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

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Securify: Practical security analysis of smart contracts,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.377088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8b2beb1a-e4b3-4c51-bb5a-57687585e6f0 · outbound

This paper cites Codebert: A pre-trained model for programming and natural languages,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Codebert: A pre-trained model for programming and natural languages,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.359425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7ac2fc66-521b-4db4-b3e5-85ab7c507952 · outbound

This paper cites Reentrancy vulnerability detection and localization: A deep learning based two-phase approach,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Reentrancy vulnerability detection and localization: A deep learning based two-phase approach,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.343987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6bde5636-90d7-4af9-bde9-4a3209dfea9e · outbound

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

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Combining Fine-Tuning and LLM-based Agents for Intuitive Smart Contract Auditing with Justifications

Reference 44

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Observation 3aaf22e2-8668-4590-88f1-5a7c964f5270 · outbound

This paper cites Towards Safer Smart Contracts: A Sequence Learning Approach to Detecting Security Threats.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Towards Safer Smart Contracts: A Sequence Learning Approach to Detecting Security Threats

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T11:52:40.904934Z

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Observation 32ea2d82-9d1e-4937-987d-8ba3a2bc240b · outbound

This paper cites Deepcrceval: Revisiting the evaluation of code review comment generation,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Deepcrceval: Revisiting the evaluation of code review comment generation,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.327741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 56a4ffa1-bb03-4cae-b554-b7ce7cd51f62 · outbound

This paper cites Llama-reviewer: Advancing code review automation with large language models through parameter- efficient fine-tuning,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Llama-reviewer: Advancing code review automation with large language models through parameter- efficient fine-tuning,

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-06T11:52:40.915252Z

Source-reported events for the cited work

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Observation bde2ff3a-e106-4c87-9b73-e868c71f2095 · outbound

This paper cites Dependency-aware method naming framework with generative adversarial sampling,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Dependency-aware method naming framework with generative adversarial sampling,

Reference 48

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This paper cites SWE-bench-java: A GitHub Issue Resolving Benchmark for Java.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection SWE-bench-java: A GitHub Issue Resolving Benchmark for Java

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-06T11:52:40.926043Z

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This paper cites Optuna: A next- generation hyperparameter optimization framework,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Optuna: A next- generation hyperparameter optimization framework,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.285828Z

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Observation 7382c913-5858-4982-bbd7-6bdbe132939a · outbound

This paper cites Exploring the potential of chatgpt in automated code refinement: An empirical study,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Exploring the potential of chatgpt in automated code refinement: An empirical study,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.270135Z

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Observation 97f6f9f9-aab8-42eb-930c-cd5b607a513b · outbound

This paper cites Algorithms for hyper- parameter optimization,.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Algorithms for hyper- parameter optimization,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T11:52:41.253977Z

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Observation 2e625bfc-2ca7-44ee-b9e5-b2ccc1eb4948 · outbound

This paper cites Available: https://zenodo.org/records/16421321.

SAEL: Leveraging Large Language Models with Adaptive Mixture-of-Experts for Smart Contract Vulnerability Detection Available: https://zenodo.org/records/16421321

Reference 2025

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