Towards Understanding Deep Learning Model in Image Recognition via Coverage Test | Paper Citation Record

Observation 779f7b25-2dc9-4ed7-a0f8-efbd3870b092 · outbound

This paper cites Black-box testing of deep neural networks through test case diversity 2023.IEEE Transactions on Software Engineering49, 5, 3182–3204.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Black-box testing of deep neural networks through test case diversity 2023.IEEE Transactions on Software Engineering49, 5, 3182–3204

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.604791Z

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Observation 7af1c660-694a-4225-a24b-f739be492315 · outbound

This paper cites A systematic review on code clone detection 2019.IEEE access7, 86121–86144.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test A systematic review on code clone detection 2019.IEEE access7, 86121–86144

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.591729Z

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Observation e95b8ce8-74b6-4390-9bee-e7b8bec3fe60 · outbound

This paper cites The non-fungible token (NFT) market and its relationship with Bitcoin and Ethereum 2022.FinTech1, 3, 216–224.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test The non-fungible token (NFT) market and its relationship with Bitcoin and Ethereum 2022.FinTech1, 3, 216–224

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.578468Z

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Observation d0abd5e0-98a4-420a-81cc-9ac5eedb6f9c · outbound

This paper cites Non-fungible token (NFT) markets on the Ethereum blockchain: Temporal development, cointegration and interrelations 2023.Economics of Innovation and New Technology32, 8, 1216–1234.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Non-fungible token (NFT) markets on the Ethereum blockchain: Temporal development, cointegration and interrelations 2023.Economics of Innovation and New Technology32, 8, 1216–1234

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.564919Z

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Observation 7bc3ff12-37c6-4fcb-9cc4-28d364aabc4f · outbound

This paper cites Longformer: The Long-Document Transformer.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Longformer: The Long-Document Transformer

Reference 5

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Observation a86197a0-35ad-4446-aaf2-adb14397807e · outbound

This paper cites Formal verification of smart contracts: Short paper 2016.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Formal verification of smart contracts: Short paper 2016

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.551102Z

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Observation 515bb792-57e7-49b5-b73d-946a4ec7e529 · outbound

This paper cites Enriching word vectors with subword information 2017.Transactions of the association for computational linguistics5, 135–146.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Enriching word vectors with subword information 2017.Transactions of the association for computational linguistics5, 135–146

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.537590Z

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Observation ff12a60b-9a34-4208-a9a5-3d8176b56402 · outbound

This paper cites Enhancing smart contract vulnerability detection in dapps leveraging fine-tuned llm 2025.arXiv preprint arXiv:2504.05006.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Enhancing smart contract vulnerability detection in dapps leveraging fine-tuned llm 2025.arXiv preprint arXiv:2504.05006

Reference 8

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Observation 90156d0b-db59-4a12-9ea9-472872e8e6e2 · outbound

This paper cites SmartBugBert: BERT-Enhanced Vulnerability Detection for Smart Contract Bytecode 2025.arXiv preprint arXiv:2504.05002.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test SmartBugBert: BERT-Enhanced Vulnerability Detection for Smart Contract Bytecode 2025.arXiv preprint arXiv:2504.05002

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T22:21:47.997546Z

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Observation abb32e58-173e-4730-92d6-aef5fae4a03b · outbound

This paper cites Deepinspect: A black-box trojan detection and mitigation framework for deep neural networks.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Deepinspect: A black-box trojan detection and mitigation framework for deep neural networks

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.524784Z

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Observation ece985cb-6c30-4538-9a90-f7572fdd05de · outbound

This paper cites Rethinking Attention with Performers.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Rethinking Attention with Performers

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T22:21:48.008736Z

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Observation 6ceeee74-7d55-402a-8e57-0e11f73746a8 · outbound

This paper cites A survey on smart contract vulnerabilities: Data sources, detection and repair 2023.Information and Software Technology159, 107221.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test A survey on smart contract vulnerabilities: Data sources, detection and repair 2023.Information and Software Technology159, 107221

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.498154Z

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Observation 047574ca-edaa-42b8-8b21-12575df3daae · outbound

This paper cites SmartBugs: A Framework to Analyze Solidity Smart Contracts 2020.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test SmartBugs: A Framework to Analyze Solidity Smart Contracts 2020

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.484835Z

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Observation c6712440-d26f-4d31-997e-cf198984bb6e · outbound

This paper cites Checking Smart Contracts with Structural Code Embedding 2020.IEEE Transactions on Software Engineering.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Checking Smart Contracts with Structural Code Embedding 2020.IEEE Transactions on Software Engineering

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.471683Z

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Observation 66bf6453-5199-489c-b814-5ec93c5fda7e · outbound

This paper cites How effective are smart contract analysis tools? evaluating smart contract static analysis tools using bug injection.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test How effective are smart contract analysis tools? evaluating smart contract static analysis tools using bug injection

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.458578Z

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Observation d27a58cc-90e7-4607-b69b-59d07b53af66 · outbound

This paper cites Achecker: Statically de- tecting smart contract access control vulnerabilities 2023.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Achecker: Statically de- tecting smart contract access control vulnerabilities 2023

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.431721Z

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Observation 90970d09-deb7-4865-a2dd-7ec8ece82910 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Explaining and Harnessing Adversarial Examples

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T22:21:48.036251Z

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Observation 30ad9389-de26-4f3c-8807-cc150a028dd3 · outbound

This paper cites Deep residual learning for image recognition 2016.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Deep residual learning for image recognition 2016

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.417962Z

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Observation 42b6ccf0-5739-4a53-bf18-f5b57635ed0d · outbound

This paper cites Characterizing code clones in the ethereum smart contract ecosystem 2020.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Characterizing code clones in the ethereum smart contract ecosystem 2020

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.404153Z

Source-reported events for the cited work

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Observation 44f78c0d-727a-4e29-bd14-ce6af6f1fc6f · outbound

This paper cites Hunting vulnerable smart contracts via graph embedding based bytecode matching 2021.IEEE Transactions on Information Forensics and Security16, 2144–2156.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Hunting vulnerable smart contracts via graph embedding based bytecode matching 2021.IEEE Transactions on Information Forensics and Security16, 2144–2156

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.390477Z

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Observation 645e08b4-bdbc-4a90-b3e3-f2cb062b411a · outbound

This paper cites Characterizing the Solana NFT ecosys- tem 2024.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Characterizing the Solana NFT ecosys- tem 2024

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.376342Z

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Observation c3b41481-7da9-4380-84ce-5adf6d89c7e7 · outbound

This paper cites Neural network models and deep learning 2019.Current Biology29, 7, R231–R236.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Neural network models and deep learning 2019.Current Biology29, 7, R231–R236

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.362713Z

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Observation 23319913-5759-4276-b633-2166cd226981 · outbound

This paper cites Gradient-based learning applied to document recognition 1998.Proc.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Gradient-based learning applied to document recognition 1998.Proc

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.349036Z

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Observation db3d6681-0399-4533-bdf2-dd56a8befa7f · outbound

This paper cites Cobra: interaction-aware bytecode-level vulnerability detector for smart contracts 2024.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Cobra: interaction-aware bytecode-level vulnerability detector for smart contracts 2024

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.335042Z

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Observation 777e739a-b11e-4297-858d-295083565cfa · outbound

This paper cites Detecting Malicious Accounts in Web3 through Transaction Graph 2024.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Detecting Malicious Accounts in Web3 through Transaction Graph 2024

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.321515Z

Source-reported events for the cited work

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Observation a33809ef-f3b8-41e0-a14e-3f4b13d4c687 · outbound

This paper cites Hybrid analysis of smart contracts and malicious behaviors in ethereum 2021.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Hybrid analysis of smart contracts and malicious behaviors in ethereum 2021

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.307762Z

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Observation bad44214-a40b-4c59-9081-909fdf57dd49 · outbound

This paper cites CLUE: towards discovering locked cryptocurrencies in ethereum 2021.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test CLUE: towards discovering locked cryptocurrencies in ethereum 2021

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.294240Z

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Observation 68637299-4a27-497a-b905-a1d644ebe2da · outbound

This paper cites an unresolved cited work.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Unresolved cited work

Reference 28

Resolution: unresolved; raw_fallback, observed 2026-08-15T22:21:49.281585Z

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Observation e108a882-74b0-424e-b1f4-548c72d9239d · outbound

This paper cites ModelDiff: Testing-based DNN similarity comparison for model reuse detection 2021.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test ModelDiff: Testing-based DNN similarity comparison for model reuse detection 2021

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.268851Z

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Observation 24969b26-ae8c-475b-aa6d-6b945b808498 · outbound

This paper cites StateGuard: Detecting State Derailment Defects in Decentralized Exchange Smart Contract 2024.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test StateGuard: Detecting State Derailment Defects in Decentralized Exchange Smart Contract 2024

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.255615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 46677bf5-def2-41ce-ae9e-dac3dc832689 · outbound

This paper cites SCALM: Detecting Bad Practices in Smart Contracts Through LLMs 2025.arXiv preprint arXiv:2502.04347.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test SCALM: Detecting Bad Practices in Smart Contracts Through LLMs 2025.arXiv preprint arXiv:2502.04347

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-15T22:21:48.092074Z

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Observation f06ba1dd-dc42-46f6-8f88-9b2fe153db4f · outbound

This paper cites On identity, transaction, and smart contract privacy on permissioned and per- missionless blockchain: A comprehensive survey 2024.Comput.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test On identity, transaction, and smart contract privacy on permissioned and per- missionless blockchain: A comprehensive survey 2024.Comput

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.242328Z

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Observation f149bc6f-48b9-4412-ba95-c4c795968b8e · outbound

This paper cites SoK: Security Analysis of Blockchain-based Cryptocurrency.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test SoK: Security Analysis of Blockchain-based Cryptocurrency

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T22:21:48.099395Z

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Observation 761d4f15-dee7-4e95-86c7-896d83940e29 · outbound

This paper cites GasTrace: Detecting Sand- wich Attack Malicious Accounts in Ethereum 2024.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test GasTrace: Detecting Sand- wich Attack Malicious Accounts in Ethereum 2024

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.227647Z

Source-reported events for the cited work

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Observation 8b956032-4a44-42e8-a84c-f9c36b541b92 · outbound

This paper cites Deepgauge: Multi-granularity testing criteria for deep learning systems 2018.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Deepgauge: Multi-granularity testing criteria for deep learning systems 2018

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.213924Z

Source-reported events for the cited work

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Observation 117d6354-3116-425b-8ac9-c2ad2efec4ba · outbound

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

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Combining Fine-Tuning and LLM-based Agents for Intuitive Smart Contract Auditing with Justifications

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-15T22:21:48.111072Z

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Observation 78cf3a7a-33c1-42ae-abc3-78cd41c3a599 · outbound

This paper cites an unresolved cited work.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Unresolved cited work

Reference 37

Resolution: unresolved; raw_fallback, observed 2026-08-15T22:21:49.199971Z

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Observation f886d3c5-b33e-47a9-b8bb-cde20def4343 · outbound

This paper cites SCLA: Automated Smart Contract Summarization via LLMs and Control Flow Prompt.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test SCLA: Automated Smart Contract Summarization via LLMs and Control Flow Prompt

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-15T22:21:48.118747Z

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Observation 17b61bfd-a8c2-4f93-a36c-5c909aab09ec · outbound

This paper cites Efficient Estimation of Word Representations in Vector Space.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Efficient Estimation of Word Representations in Vector Space

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-15T22:21:48.122827Z

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Observation 9700f2e8-3f03-46cb-b589-ef0ea1d65299 · outbound

This paper cites Mapping the NFT revolution: market trends, trade networks, and visual features 2021.Scientific reports11, 1, 20902.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Mapping the NFT revolution: market trends, trade networks, and visual features 2021.Scientific reports11, 1, 20902

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.186680Z

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Observation 084bfe09-39d0-423d-bf4c-c6cdc08eb35c · outbound

This paper cites Understanding source code evolution using abstract syntax tree matching 2005.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Understanding source code evolution using abstract syntax tree matching 2005

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.173210Z

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Observation de660cbf-aff0-4374-94e7-58fe4a8af29f · outbound

This paper cites Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-15T22:21:48.134721Z

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Observation 11d2a465-c2f8-46c9-b27b-16e873dc9425 · outbound

This paper cites Unveiling wash trading in popular NFT markets 2024.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Unveiling wash trading in popular NFT markets 2024

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.159555Z

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Observation 69ed1b8c-0948-4c8c-8a4a-3962d95d7e00 · outbound

This paper cites Enhancing Ethereum smart-contracts static analysis by computing a precise Control-Flow Graph of Ethereum bytecode 2023.Journal of Systems and Software200, 111653.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Enhancing Ethereum smart-contracts static analysis by computing a precise Control-Flow Graph of Ethereum bytecode 2023.Journal of Systems and Software200, 111653

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.145161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 89df1304-d9ca-4262-be81-7fb105d8bb3e · outbound

This paper cites Deepxplore: Automated whitebox testing of deep learning systems 2017.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Deepxplore: Automated whitebox testing of deep learning systems 2017

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.131414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e0e357b7-163c-460d-875a-f1f659ce189e · outbound

This paper cites Smart Contract Vulnerability Detection Technique: A Survey.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Smart Contract Vulnerability Detection Technique: A Survey

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-15T22:21:48.151178Z

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Observation b88a5d30-14b2-445f-8fe2-73887776e0dc · outbound

This paper cites Sourcerercc: Scaling code clone detection to big-code 2016.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Sourcerercc: Scaling code clone detection to big-code 2016

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.116491Z

Source-reported events for the cited work

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Observation cd0175ed-49c5-4ce7-bb44-ba5d6582e1fd · outbound

This paper cites An empirical study on test case prioritization metrics for deep neural networks 2021.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test An empirical study on test case prioritization metrics for deep neural networks 2021

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.103634Z

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Observation 00f9ccac-6531-4966-bc14-99a906e24de2 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-15T22:21:48.163591Z

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Observation fd322528-0ec1-4afe-ae06-375d46c4f27b · outbound

This paper cites Fast Graph Attention Networks Using Effective Resistance Based Graph Sparsification.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Fast Graph Attention Networks Using Effective Resistance Based Graph Sparsification

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-15T22:21:48.168027Z

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Observation ccd6c7c5-1c37-4779-920a-0a316c0c148f · outbound

This paper cites Testing Deep Neural Networks.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Testing Deep Neural Networks

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-15T22:21:48.172376Z

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Unavailable: canonical work link unavailable.

Observation 00b9abd4-3e34-4eca-8946-c857ad6d001e · outbound

This paper cites DeepConcolic: Testing and debugging deep neural networks.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test DeepConcolic: Testing and debugging deep neural networks

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.090645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 52d24046-695d-4b03-bf4b-5d66d6903d59 · outbound

This paper cites Structural test coverage criteria for deep neural networks 2019.ACM Transactions on Embedded Computing Systems (TECS)18, 5s, 1–23.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Structural test coverage criteria for deep neural networks 2019.ACM Transactions on Embedded Computing Systems (TECS)18, 5s, 1–23

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.064317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 48b405bf-04f9-4163-b10e-e6413d6abef4 · outbound

This paper cites Smart contracts: building blocks for digital markets 1996.EXTROPY: The Journal of Transhumanist Thought,(16)18, 2, 28.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Smart contracts: building blocks for digital markets 1996.EXTROPY: The Journal of Transhumanist Thought,(16)18, 2, 28

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.051616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 60819138-89bf-4283-b65e-2dabc0ff071d · outbound

This paper cites an unresolved cited work.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Unresolved cited work

Reference 55

Resolution: unresolved; raw_fallback, observed 2026-08-15T22:21:49.076814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7093676e-1537-48fe-ad96-eeafb899eebb · outbound

This paper cites Smartcheck: Static analysis of ethereum smart contracts 2018.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Smartcheck: Static analysis of ethereum smart contracts 2018

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.024033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 704dafcb-9260-4507-80e3-cb4acc3a0ab2 · outbound

This paper cites A survey of smart contract formal specification and verification 2021.ACM Computing Surveys (CSUR)54, 7, 1–38.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test A survey of smart contract formal specification and verification 2021.ACM Computing Surveys (CSUR)54, 7, 1–38

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.010480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 295b8c69-a528-4be2-9bd5-f5dd6772df3b · outbound

This paper cites Ethereum Smart Contract Representation Learning for Robust Bytecode-Level Similarity Detection.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Ethereum Smart Contract Representation Learning for Robust Bytecode-Level Similarity Detection

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:49.037355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 62e09d44-e8fe-4e99-9979-72706f2811af · outbound

This paper cites Non-Fungible Token (NFT): Overview, Evaluation, Opportunities and Challenges.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Non-Fungible Token (NFT): Overview, Evaluation, Opportunities and Challenges

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-15T22:21:48.214103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 696314b4-e204-4e24-8ab2-91e80a751b88 · outbound

This paper cites Smart contracts in the real world: A statistical exploration of external data dependencies 2024.arXiv preprint arXiv:2406.13253.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Smart contracts in the real world: A statistical exploration of external data dependencies 2024.arXiv preprint arXiv:2406.13253

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-15T22:21:48.218925Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19ed1513-447a-4498-8f6b-037858e4ce26 · outbound

This paper cites Securify: Practical security analysis of smart con- tracts 2018.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Securify: Practical security analysis of smart con- tracts 2018

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:48.996928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d2fab646-e1f2-4d00-a376-fb5575318b3b · outbound

This paper cites WakeMint: Detecting Sleep- minting Vulnerabilities in NFT Smart Contracts 2025.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test WakeMint: Detecting Sleep- minting Vulnerabilities in NFT Smart Contracts 2025

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:48.970682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e5906fdc-050e-4a66-98c8-9795a8f4b87a · outbound

This paper cites Npc: Neuron path coverage via characterizing decision logic of deep neural 9 Conference’17, July 2017, Washington, DC, USA Wenkai and Xiaoqi, et al.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Npc: Neuron path coverage via characterizing decision logic of deep neural 9 Conference’17, July 2017, Washington, DC, USA Wenkai and Xiaoqi, et al

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:48.956998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation bf077917-42e6-4ca4-89ab-85e5d31e9dbc · outbound

This paper cites Deep learning code fragments for code clone detection 2016.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Deep learning code fragments for code clone detection 2016

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:48.983976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8b39072a-ce50-4b64-a73a-da2018ed060f · outbound

This paper cites Correlations between deep neural network model coverage criteria and model quality 2020.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Correlations between deep neural network model coverage criteria and model quality 2020

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:48.926003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b166b666-2689-48a5-af5a-b340c20e3f56 · outbound

This paper cites Un- cover the premeditated attacks: Detecting exploitable reentrancy vulnerabilities by identifying attacker contracts 2024.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Un- cover the premeditated attacks: Detecting exploitable reentrancy vulnerabilities by identifying attacker contracts 2024

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:48.911241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 23d15dd3-69dc-4abf-99e1-6da61f326250 · outbound

This paper cites Deephunter: a coverage-guided fuzz testing framework for deep neural networks 2019.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Deephunter: a coverage-guided fuzz testing framework for deep neural networks 2019

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:48.942647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 16e71f73-c67e-4fbe-8b12-4c2d03fd0cb8 · outbound

This paper cites Combining GPT and Code-Based Similarity Checking for Effective Smart Contract Vulnerability Detection.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Combining GPT and Code-Based Similarity Checking for Effective Smart Contract Vulnerability Detection

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-15T22:21:48.252508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c48dd57-0413-4df2-b5ec-986d3d5d8da6 · outbound

This paper cites ACFIX: Guiding LLMs with Mined Common RBAC Practices for Context-Aware Repair of Access Control Vulnerabilities in Smart Contracts.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test ACFIX: Guiding LLMs with Mined Common RBAC Practices for Context-Aware Repair of Access Control Vulnerabilities in Smart Contracts

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-15T22:21:48.256637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7fe1c075-9ec6-4463-bc11-16be7d0adb8e · outbound

This paper cites Revisiting neuron coverage for dnn testing: A layer-wise and distribution-aware criterion 2023.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Revisiting neuron coverage for dnn testing: A layer-wise and distribution-aware criterion 2023

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:48.896421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 65e45761-78c7-428c-ad9a-ee3bb756090a · outbound

This paper cites Byte- code similarity detection of smart contract across optimization options and compiler versions based on triplet network 2022.Electronics11, 4, 597.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Byte- code similarity detection of smart contract across optimization options and compiler versions based on triplet network 2022.Electronics11, 4, 597

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:48.864477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 245fa38c-1a71-4d7d-8065-ebcc0fe73ba4 · outbound

This paper cites Malicious Code Detection in Smart Contracts via Opcode Vectorization 2025.arXiv preprint arXiv:2504.12720.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Malicious Code Detection in Smart Contracts via Opcode Vectorization 2025.arXiv preprint arXiv:2504.12720

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-15T22:21:48.268251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b4ef592-81c5-4853-b7a2-2fcf823e93e0 · outbound

This paper cites PrettySmart: Detecting Permission Re-delegation Vulnerability for To- ken Behaviors in Smart Contracts 2024.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test PrettySmart: Detecting Permission Re-delegation Vulnerability for To- ken Behaviors in Smart Contracts 2024

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:21:48.880679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5aa1626c-6fb0-4274-8e77-447dd0f55338 · outbound

This paper cites an unresolved cited work.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Unresolved cited work

Reference 2019

Resolution: unresolved; raw_fallback, observed 2026-08-15T22:21:49.511354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b0e46ce5-8100-4c29-b2b4-f7860b55ccba · outbound

This paper cites an unresolved cited work.

Towards Understanding Deep Learning Model in Image Recognition via Coverage Test Unresolved cited work

Reference 2020

Resolution: unresolved; raw_fallback, observed 2026-08-15T22:21:49.444900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers