Pith. sign in

REVIEW 4 major objections 5 minor 1 cited by

Understanding NFTs from EIP Standards

T0 review · 4 major / 5 minor · reviewed 2026-08-05 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗

Pith's one-line read This paper claims that NFTs are best understood through their EIP standards, and that a corpus-level analysis of 191 proposals reveals a few foundational interfaces dominating reuse while newer, more complex standards widen the security ris

desk verdict First real map of the NFT standards layer, but the corpus and parser are not yet auditable and two abstract claims outrun the evidence. read the letter →

arxiv 2508.07190 v1 pith:HDAE5IY3 submitted 2025-08-10 cs.CR cs.ET

Minfeng Qi , Qin Wang , Guangsheng Yu , Ruiqiang Li , Victor Zhou , Shiping Chen This is my paper · ORCID
classification cs.CRcs.ET
keywords NFTstandardsEthereumImprovementProposalsERCinterfacesSolidityinterfaceparsingtokenstandardizationsecuritycontributoranalysisblockchainempiricalstudy
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper argues that the technical backbone of NFTs—the Ethereum Improvement Proposals that define them—can and should be studied as a corpus, and that doing so reveals the ecosystem's structure. It filters 213 NFT-related EIPs, parses 1,572 Solidity interface functions from 191 of them, and builds an inheritance graph that shows a core-centric landscape: ERC-165 and ERC-721 are the dominant hubs, a small set of functions such as balanceOf and safeTransferFrom is reused across standards, and later proposals mostly add specialized extensions on top. The data also shows a bifurcated and selective pipeline (30% Draft, 30% Final, 27.7% Stagnant), a contributor base dominated by single-author proposals and a small recurring core, and limited interface reuse across versions—the paper's evidence for poor cross-version interoperability. Finally, it argues that security risk grows with functional complexity: ERC-721 and ERC-1155 have bounded, known vulnerabilities, while ERC-6551 and newer extensions introduce enforcement gaps that contract-level checks alone cannot close. A reader should care because this is the first systematic map of the layer that defines what an NFT actually is, and it locates where interoperability and risk are concentrated.

What carries the argument

The carrying object is the EIP corpus treated as a structural dataset. The pipeline has three parts: a keyword filter using terms such as 'nft' and 'non-fungible' plus a manual confirmation round that selects 213 NFT-related proposals; automated parsing of embedded Solidity interfaces with HTML parsing and regular expressions, extracting 1,572 functions with parameter types, return types, and declared inheritance edges; and a time-anchored inheritance graph in which nodes are standards, edges are declared inheritance or extension relations, and node size encodes in-degree centrality. That graph is what turns a list of documents into a map: it is the mechanism by which foundational standards

What would settle it

Take the same EIP corpus, have independent annotators hand-label NFT relevance and hand-parse a random sample of the 191 interfaces, then compare precision and recall of the keyword filter and the extracted 1,572 function signatures against that gold standard. A material disagreement rate would overturn the RQ1–RQ4 statistics; so would finding an NFT-related EIP absent from the 213/191 set or a parsed inheritance edge that contradicts the official EIP text.

Watch

Extended reading notes

Core claim

The paper claims the NFT ecosystem has a measurable standardization substrate: 213 NFT-related EIPs, 191 with Solidity interfaces, yielding 1,572 parsed functions. The stage distribution is bifurcated (30% Draft, 30% Final, 27.7% Stagnant), the inheritance graph is core-centric—ERC-165 and ERC-721 are hubs—and reuse concentrates on a few primitives like balanceOf, safeTransferFrom, and ownerOf. Contributor data shows 76 single-author proposals and 379 of 445 authors contributing once. The paper also argues security risk scales with complexity, with ERC-6551 and extensions like ERC-4907, ERC-4675, and ERC-2981 introducing enforcement gaps beyond the contract itself.

Load-bearing premise

Everything rests on the dataset being complete and correctly parsed: if some NFT-related proposals were missed or interface functions were misread, the stage percentages, function-reuse counts, centrality rankings, and risk conclusions would all shift.

Editorial extensions

If this is right

  • If the map is correct, new NFT standards that do not inherit from ERC-165 or ERC-721 or reuse the dominant primitives will face interoperability friction, because wallets, marketplaces, and indexers are built around those hubs.
  • The 30% Final and 27.7% Stagnant split implies that most proposed NFT functionality never reaches adoption; standards that clear Draft are the exception, and community attention is the binding constraint.
  • Because 76 of 213 EIPs are single-author and 379 of 445 authors contribute once, standardization depends on a small recurring core; over 65% of proposals come from unaffiliated individuals.
  • Security risk is not uniform across standards: ERC-6551's token-bound account model and extensions such as ERC-4907, ERC-4675, and ERC-2981 shift the attack surface from the NFT contract to interactions, shared implementations, and off-chain enforcement.
  • Academic NFT research is misaligned with the standard landscape: studies concentrate on ERC-721 market data, while ERC-1155 and post-2021 standards remain empirically underexamined.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • The same corpus-level lens could be turned on fungible-token standards (the ERC-20 family) or on Bitcoin-native token proposals to test whether the core-centric, high-stagnation, single-author-heavy pattern is a general property of token standardization or specific to NFTs.
  • The paper's risk analysis is built on secondary sources; a direct test would be to scan deployed ERC-6551 and ERC-4907 contracts for the named vulnerability patterns—asset draining before sale, shared-implementation flaws, missing royalty enforcement—to see whether the complexity-risk correlation holds outside the standards text.
  • Because the parameter-level data is machine-readable, a practical extension is an automated compatibility checker that flags new NFT EIPs whose signatures conflict with, or fail to inherit from, the 1,572-function corpus.
  • The pseudonymity and geolocation classifications are heuristic; validating them against GitHub profiles or on-chain attribution would make the 20.4% pseudonymous figure robust enough to use in policy discussions.
Share X Bluesky LinkedIn Reddit HN

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

4 major / 5 minor

Summary. The paper claims to present the first study of NFTs through the lens of Ethereum Improvement Proposals (EIPs). The authors construct a corpus of 213 NFT-related EIPs (191 with Solidity interfaces), parse 1,572 interface functions, build an inheritance graph centered on ERC-165/ERC-721, profile 445 contributors, and mine Ethereum Magicians discussions. They describe a bifurcated stage distribution, a core-centric inheritance topology, skewed contributor and engagement patterns, and a qualitative security assessment of ERC-721, ERC-1155, ERC-6551 and emerging proposals. The stated contributions are: the structural landscape of NFT standards, a socio-technical perspective on standardization, and a synthesis of academic coverage and security challenges.

Significance. If the dataset construction and parsing are sound, this would be a useful structured map of the NFT standardization ecosystem, and the RQ decomposition is a sensible organizing device. The paper usefully distinguishes foundational from emerging standards and quantifies function reuse and inheritance concentration. However, the magnitude of the contribution is currently bounded by two unverified pillars: the corpus/parser fidelity and the qualitative security claim. The paper would be substantially strengthened by releasing the dataset and validation artifacts, and by either sharply scaling back or rigorously supporting the 'growing functional complexity heightens security risks' assertion.

major comments (4)
  1. [§IV.B / Table III] The counts that anchor the paper—213/191 EIPs, 1,572 functions, stage percentages, and the inheritance graph—depend entirely on the keyword+manual selection and regex-based parsing described in §IV.B. No validation set, annotation protocol, parser error rate, or inter-annotator agreement is reported; Table III states the datasets 'will be released once this work is finalized.' Regex parsing of Solidity is fragile with respect to multi-line signatures, comments/strings containing 'function', inherited declarations, and interface-vs-implementation blocks. Because every RQ1–RQ4 statistic inherits these choices, I ask for release of the datasets and a validation/error analysis, or at least a conservative sensitivity analysis.
  2. [§VI.B / Abstract] The abstract's claim that the paper 'show[s] that growing functional complexity heightens security risks' is not supported by the presented evidence. §VI.B and Table V are qualitative, and many vulnerability attributions rely on blog posts or industry articles ([61]–[69], [71]–[74]) rather than systematic measurements. No complexity metric or risk metric is operationalized, and no correlation is computed. The internal inconsistency between §VI.B's description of ERC-4675 as supporting fractional ownership and Table VI's listing of EIP-4675 as 'Token URI JSON Schema' further indicates that this review needs reworking. Please reframe as a scoped qualitative review or provide rigorous empirical support.
  3. [Abstract / RQ3 / Fig. 5] The abstract says the paper 'expose[s] poor cross-version interoperability,' but no operational definition of interoperability is given and no compatibility metric is measured. Fig. 5 and the RQ3 discussion show inheritance/extension edges, which are not equivalent to interoperability. The paper should either define and measure cross-version interoperability explicitly or soften this claim to 'limited interface reuse among standards.'
  4. [§V.E] The real-name/pseudonym heuristic and the geolocation classification are not validated. The distinction between 'Real Name' and 'Pseudonym' is based on 'plausibly corresponds' with no operational criteria, and the geographic distribution rests on self-reported GitHub locations with 24.2% of contributors excluded. The specific numbers (78.2%/21.8%, 22.6% US, etc.) should be presented as heuristics, and the classification rules should be released so the robustness of RQ5 can be assessed.
minor comments (5)
  1. [Throughout] The manuscript contains many corrupted placeholder symbols (e.g., 'balanceOf', 'approve', 'tokenURI' appear as ���������) and incomplete references, notably [42] 'Author of the forum post', [68] 'Author(s) listed on the EIP page', and [70] 'Year of creation'. These must be fixed before any publication.
  2. [§IV.B / Table III] The relationship between the 'over 10,000 discussion entries' from 39 EIP + 11 ERC pages and the 121 NFT EIP topics in Table III is unclear. Please explain the filtering steps and counts.
  3. [Fig. 5] Figure 5 is difficult to read: node labels are too small and many edges are indistinguishable. A zoomable or summarized version would help the reader verify the core-centric inheritance claim.
  4. [Table V] Table V includes a 'Color legend' but the table is rendered as text; if colors are not visible in the final format, replace the legend with explicit textual labels.
  5. [§VI.B] The security discussion cites several blog posts as primary evidence (e.g., [62], [63], [65], [66]). Prefer peer-reviewed or official references for claims about standard-level vulnerabilities, or explicitly label the evidence base as community sources.

Circularity Check

0 steps flagged · score 1.0 of 10

No significant circularity: the paper is an observational corpus study whose headline findings are direct aggregates of parsed EIP data, not fitted predictions.

full rationale

This is an empirical, observational study rather than a derivation, so the classic circularity failure modes do not apply. The central results (213 NFT-related EIPs, 1,572 parsed interface functions, stage distributions, inheritance centrality, contributor statistics) are direct aggregations of the EIP corpus and the authors' parsing pipeline; no parameter is fitted to a subset and then used to predict a closely related quantity. The 'foundational' designation of ERC-165/ERC-721 is an operational characterization based on in-degree centrality in the constructed inheritance graph, not an independent prediction. The security-risk discussion is a qualitative synthesis of secondary sources and does not reduce to a fitted model or a self-citation. The paper's self-citations ([1], [34]-[39], [50], [53], [38]) appear in related-work and background contexts; none is load-bearing for the headline empirical claims. The reproducibility concern about corpus selection and regex parsing is a validity/auditability issue, not circularity. Overall, no circular step can be exhibited by quoting a specific equation or reduction.

Assumptions & free parameters 0 free parameters · 6 assumptions · 0 invented entities

This is an empirical measurement paper, so there are no fitted parameters and no invented entities. What the analysis rests on is a chain of data-construction assumptions: the corpus definition, parse fidelity, manual taxonomies, identity heuristics, and the representative-ness of forum and secondary-source material. Each assumption is reasonable for a descriptive study but unverified, and the abstract's causal-sounding security claim depends on the weakest of them.

assumptions (6)
  • domain assumption The keyword-based filter plus a manual confirmation round correctly identifies all and only NFT-related EIPs (213 candidates, 191 with interfaces).
    Section IV.B defines the population; every downstream count and distribution (RQ1-RQ5) is conditional on this selection.
  • domain assumption Regex-based parsing of Solidity interface code recovers function signatures, parameter types, and inheritance relationships without material error.
    Section IV.B; parsing output (1,572 functions) feeds the function taxonomy, parameter analysis, and inheritance graph of RQ2-RQ4.
  • domain assumption The five-category function taxonomy (data management, relationship and listing, access and permission, attribute settings, registration and licensing) is applied consistently.
    Section V.B; the claim that data management dominates (584 of 1,572 functions) depends on a manual classification not validated by independent coders.
  • domain assumption Author identifiers heuristically classified as real names vs pseudonyms, and self-reported GitHub locations, approximate true contributor identity and geography.
    Section V.E; 107 of 445 authors (24.2%) ungeolocatable were excluded, and the 78.2% real-name share rests on an unvalidated heuristic.
  • domain assumption Ethereum Magicians forum threads retrieved via the public API are a representative sample of NFT EIP community discussion.
    Section IV.B; engagement statistics (median 6 replies, 5 participants) and the 'concentrated debate' insight depend on forum crawl completeness.
  • domain assumption Secondary sources (practitioner blog posts and audit guides) cited in Section VI.B accurately characterize intrinsic vulnerabilities of the reviewed standards.
    RQ7's conclusion that functional complexity heightens security risk is built on references [61]-[74], mostly non-peer-reviewed.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Understanding NFTs from EIP Standards." pith.science (2026). https://pith.science/paper/HDAE5IY3

@misc{pith2026250807190,
  author       = {Pith},
  title        = {Pith review of: Understanding NFTs from EIP Standards},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/HDAE5IY3}},
  note         = {Machine review of arXiv:2508.07190}
}
read the original abstract

We argue that the technical foundations of non-fungible tokens (NFTs) remain inadequately understood. Prior research has focused on market dynamics, user behavior, and isolated security incidents, yet systematic analysis of the standards underpinning NFT functionality is largely absent. We present the first study of NFTs through the lens of Ethereum Improvement Proposals (EIPs). We conduct a large-scale empirical analysis of 191 NFT-related EIPs and 10K+ Ethereum Magicians discussions (as of July, 2025). We integrate multi-dimensional analyses including the automated parsing of Solidity interfaces, graph-based modeling of inheritance structures, contributor profiling, and mining of community discussion data. We distinguish foundational from emerging standards, expose poor cross-version interoperability, and show that growing functional complexity heightens security risks.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Counted NFT Transfers

    cs.CR 2026-02 conditional novelty 6.0 of 10

    ERC-7634 is a minimal, backward-compatible standard that lets an NFT be transferred at most L times; the paper argues the remaining budget is priced value that deters wash trading and bounds leverage.

Reference graph

Works this paper leans on

74 extracted references · 71 canonical work pages · cited by 1 Pith paper

  1. [61]

    What is a reentrancy attack in solidity smart contracts? Blog Post

    Cyfrin. What is a reentrancy attack in solidity smart contracts? Blog Post

    work page

  2. [69]

    How are NFT rentals redefining ownership in the digital world

    Debut Infotech. How are NFT rentals redefining ownership in the digital world. Blog Post

    work page

  3. [71]

    What are fractional NFTs? - platforms, token & risks

    Dmitry K. What are fractional NFTs? - platforms, token & risks. Blog Post, July 2023

    work page 2023

  4. [74]

    Exploring the NFT royalty standard (EIP-2981)

    Blaine Malone. Exploring the NFT royalty standard (EIP-2981). Blog Post, August 2021. 16 TABLE VI: NFT-related ERCs with Final Status (Updated on Aug. 2025) EIP- Title Main (new) functions/events/metadata Feature Application (A) Core NFT Standards 721 Non-Fungible Token Standard ownerOf, safeTransferFrom, approve Unique on-chain assets Art, Collectibles 1...

    work page 2021

  5. [1]

    Non-fungible token (NFT): Overview, evaluation, opportunities and challenges

    Qin Wang, Rujia Li, Qi Wang, and Shiping Chen. Non-fungible token (NFT): Overview, evaluation, opportunities and challenges. arXiv preprint arXiv:2105.07447, 2021

    arXiv 2021

  6. [2]

    Exploring Web3 From the View of Blockchain

    Qin Wang, Rujia Li, Qi Wang, Shiping Chen, Mark Ryan, and Thomas Hardjono. Exploring Web3 from the view of blockchain. arXiv preprint arXiv:2206.08821, 2022

    work page Pith review arXiv 2022

  7. [3]

    Do NFTs’ owners really possess their assets? a first look at the NFT-to-asset connection fragility

    Ziwei Wang, Jiashi Gao, and Xuetao Wei. Do NFTs’ owners really possess their assets? a first look at the NFT-to-asset connection fragility. In Proceedings of the ACM Web Conference (WWW), pages 2099–2109, 2023

    work page

  8. [4]

    Non-fungible token (NFT) global market report, 2023

    The Business Research Company. Non-fungible token (NFT) global market report, 2023. Accessed: July 2025

    work page 2023

Show all 74 references
  1. [5]

    NFT market growth statistics 2025: How big is the NFT market? Webpage, August 2025

    CoinLaw. NFT market growth statistics 2025: How big is the NFT market? Webpage, August 2025

    2025

  2. [6]

    Dapp industry report – 2024 overview

    Sara Gherghelas. Dapp industry report – 2024 overview. Blog Post, January 2025

    2024

  3. [7]

    State of blockchain gaming in q1 2024

    Sara Gherghelas. State of blockchain gaming in q1 2024. Blog Post, April 2024

    2024

  4. [8]

    Eip- 721: Non-fungible token standard

    William Entriken, Dieter Shirley, Jacob Evans, Nastassia Sachs. Eip- 721: Non-fungible token standard. Technical Report 721, Ethereum Improvement Proposals, January 2018. Status: Final

    2018

  5. [9]

    and Ronan Sandford

    Witek Radomski, Andrew Cooke, Philippe Castonguay, James Therien, Eric B. and Ronan Sandford. Eip-1155: Multi-token standard. Technical Report 1155, Ethereum Improvement Proposals, June 2018. Status: Final

    2018

  6. [10]

    Show me your NFT and i tell you how it will perform: Multimodal representation learning for nft selling price prediction

    Davide Costa, Lucio La Cava, and Andrea Tagarelli. Show me your NFT and i tell you how it will perform: Multimodal representation learning for nft selling price prediction. In Proceedings of the ACM Web Conference (WWW), pages 1875–1885, 2023

    2023

  7. [11]

    Unveiling wash trading in popular NFT markets

    Yuanzheng Niu, Xiaoqi Li, Hongli Peng, and Wenkai Li. Unveiling wash trading in popular NFT markets. In Companion Proceedings of the ACM on Web Conference (Workshop@WWW), pages 730–733, 2024

    2024

  8. [12]

    Tweetboost: Influence of social media on NFT valuation

    Arnav Kapoor, Dipanwita Guhathakurta, Mehul Mathur, Rupanshu Yadav, Manish Gupta, and Ponnurangam Kumaraguru. Tweetboost: Influence of social media on NFT valuation. In Companion Proceedings of the Web Conference (Workshop@WWW) , pages 621–629, 2022

    2022

  9. [13]

    Miracle or mirage? a measurement study of NFT rug pulls

    Jintao Huang, Ningyu He, Kai Ma, Jiang Xiao, and Haoyu Wang. Miracle or mirage? a measurement study of NFT rug pulls. Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS), 7(3):1–25, 2023

    2023

  10. [14]

    Definition and detection of defects in NFT smart contracts

    Shuo Yang, Jiachi Chen, and Zibin Zheng. Definition and detection of defects in NFT smart contracts. In Proceedings of the ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA) , pages 373–384, 2023

    2023

  11. [15]

    Demys- tifying Web3 centralization: The case of off-chain NFT hijacking

    Felix St ¨oger, Anxin Zhou, Huayi Duan, and Adrian Perrig. Demys- tifying Web3 centralization: The case of off-chain NFT hijacking. In International Conference on Financial Cryptography and Data Security (FC), pages 182–199. Springer, 2023

    2023

  12. [16]

    ARTEMIS: Detecting airdrop hunters in NFT markets with a graph learning system

    Chenyu Zhou, Hongzhou Chen, Hao Wu, Junyu Zhang, and Wei Cai. ARTEMIS: Detecting airdrop hunters in NFT markets with a graph learning system. In Proceedings of the ACM on Web Conference (WWW), pages 1824–1834, 2024

    2024

  13. [17]

    ”centralized or decentralized?”: Concerns and value judgments of stakeholders in the non-fungible tokens (NFTs) market

    Yunpeng Xiao, Bufan Deng, Siqi Chen, Kyrie Zhixuan Zhou, Ray LC, Luyao Zhang, and Xin Tong. ”centralized or decentralized?”: Concerns and value judgments of stakeholders in the non-fungible tokens (NFTs) market. Proceedings of the ACM on Human-Computer Interaction , 8(CSCW1):1...

    2024

  14. [18]

    Towards more secure interactions: Understanding user experience and behaviour in the NFT domain

    Wei Lee Yuan Chen. Towards more secure interactions: Understanding user experience and behaviour in the NFT domain. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (Workshop@CHI), pages 1–10, 2024

    2024

  15. [19]

    NFT wash trading: Quantifying suspicious behaviour in NFT markets

    Victor von Wachter, Johannes Rude Jensen, Ferdinand Regner, and Omri Ross. NFT wash trading: Quantifying suspicious behaviour in NFT markets. In International Conference on Financial Cryptography and Data Security (FC) , pages 299–311. Springer, 2022

    2022

  16. [20]

    Understanding security issues in the NFT ecosystem

    Dipanjan Das, Priyanka Bose, Nicola Ruaro, Christopher Kruegel, and Giovanni Vigna. Understanding security issues in the NFT ecosystem. In Proceedings of the ACM SIGSAC Conference on Computer and Communications Security (CCS) , pages 667–681, 2022

    2022

  17. [21]

    Uncovering NFT domain-specific defects on smart contract bytecode

    Zuchao Ma, Muhui Jiang, Xiapu Luo, Haoyu Wang, and Yajin Zhou. Uncovering NFT domain-specific defects on smart contract bytecode. IEEE Transactions on Dependable and Secure Computing , 2025

    2025

  18. [22]

    Unknown threats detection methods of smart contracts

    Daojing He, Ke Ding, Sammy Chan, and Mohsen Guizani. Unknown threats detection methods of smart contracts. IEEE Internet of Things Journal, 11(3):4430–4441, 2023

    2023

  19. [23]

    Wakemint: Detecting sleepminting vulnerabilities in NFT smart contracts

    Lei Xiao, Shuo Yang, Wen Chen, and Zibin Zheng. Wakemint: Detecting sleepminting vulnerabilities in NFT smart contracts. In 2025 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER), pages 740–750. IEEE, 2025. 15

    2025

  20. [24]

    Ai-based vulnerability analysis of NFT smart contracts

    Xin Wang and Xiaoqi Li. Ai-based vulnerability analysis of NFT smart contracts. arXiv preprint arXiv:2504.16113 , 2025

    2025

  21. [25]

    A game of NFTs: Characterizing NFT wash trading in the Ethereum blockchain

    Massimo La Morgia, Alessandro Mei, Alberto Maria Mongardini, and Eugenio Nerio Nemmi. A game of NFTs: Characterizing NFT wash trading in the Ethereum blockchain. In IEEE International Conference on Distributed Computing Systems (ICDCS) , pages 13–24. IEEE, 2023

    2023

  22. [26]

    Identifying washtrading cases in NFT sales networks

    Nargess Tahmasbi, Guohou Shan, and Aaron M French. Identifying washtrading cases in NFT sales networks. IEEE Transactions on Computational Social Systems (TCSS) , 2023

    2023

  23. [27]

    NFTDisk: Visual detection of wash trading in NFT markets

    Xiaolin Wen, Yong Wang, Xuanwu Yue, Feida Zhu, and Min Zhu. NFTDisk: Visual detection of wash trading in NFT markets. In Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI), pages 1–15, 2023

    2023

  24. [28]

    Live graph lab: towards open, dynamic and real transaction graphs with NFT

    Zhen Zhang, Bingqiao Luo, Shengliang Lu, and Bingsheng He. Live graph lab: towards open, dynamic and real transaction graphs with NFT. Advances in Neural Information Processing Systems (NeurIPS) , 36, 2024

    2024

  25. [29]

    Characterizing the opensea NFT marketplace

    Bryan White, Aniket Mahanti, and Kalpdrum Passi. Characterizing the opensea NFT marketplace. In Companion Proceedings of the Web Conference (Workshop@WWW), pages 488–496, 2022

    2022

  26. [30]

    Characterizing the solana NFT ecosystem

    Dechao Kong, Xiaoqi Li, and Wenkai Li. Characterizing the solana NFT ecosystem. In Companion Proceedings of the ACM on Web Conference (Workshop@WWW), pages 766–769, 2024

    2024

  27. [31]

    Predicting NFT classification with GNN: A recommender system for web3 assets

    Guangsheng Yu, Qin Wang, Tanzeela Altaf, Xu Wang, Xiwei Xu, and Shiping Chen. Predicting NFT classification with GNN: A recommender system for web3 assets. In IEEE International Conference on Blockchain and Cryptocurrency (ICBC) , pages 1–5. IEEE, 2023

    2023

  28. [32]

    Defi and NFTs hinder blockchain scalability

    Lioba Heimbach, Quentin Kniep, Yann V onlanthen, and Roger Watten- hofer. Defi and NFTs hinder blockchain scalability. In International Conference on Financial Cryptography and Data Security (FC) , pages 291–309. Springer, 2023

    2023

  29. [33]

    Stake- holders and value in the NFT ecosystem: Towards a multi-disciplinary understanding of the nft phenomenon

    Mehmet Aydın Baytas ¸, Amos Cappellaro, and Ylva Fernaeus. Stake- holders and value in the NFT ecosystem: Towards a multi-disciplinary understanding of the nft phenomenon. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (Workshop@CHI), pages 1–8, 2022

    2022

  30. [34]

    A referable NFT scheme

    Qin Wang, Guangsheng Yu, Shange Fu, Shiping Chen, Jiangshan Yu, and Xiwei Xu. A referable NFT scheme. In IEEE International Conference on Blockchain and Cryptocurrency (ICBC) , pages 1–6. IEEE, 2023

    2023

  31. [35]

    Maximizing NFT incentives: References make you rich

    Guangsheng Yu, Qin Wang, Caijun Sun, Lam Duc Nguyen, HMN Dilum Bandara, and Shiping Chen. Maximizing NFT incentives: References make you rich. IEEE Transactions on Services Computing (TSC) , 2025

    2025

  32. [36]

    Understanding BRC- 20: Hope or hype

    Qin Wang, Guangsheng Yu, and Shiping Chen. Understanding BRC- 20: Hope or hype. IEEE Transactions on Computational Social Systems, 2025

    2025

  33. [37]

    The writing is on the wall: Analyzing the boom of inscriptions and its impact on rollup performance and cost efficiency

    Krzysztof Gogol, Johnnatan Messias, Maria In ˆes Silva, and Benjamin Livshits. The writing is on the wall: Analyzing the boom of inscriptions and its impact on rollup performance and cost efficiency. arXiv preprint arXiv:2404.11189, 2024

    2024 arXiv

  34. [38]

    Bitcoin inscriptions: Foundations and beyond

    Ningran Li, Minfeng Qi, et al. Bitcoin inscriptions: Foundations and beyond. IEEE International Conference on Blockchain and Cryptocur- rency (ICBC), 2024

    2024

  35. [39]

    Bridging BRC-20 to Ethereum

    Qin Wang, Guangsheng Yu, and Shiping Chen. Bridging BRC-20 to Ethereum. IEEE International Conference on Blockchain and Cryp- tocurrency (ICBC), pages 1–10, 2024

    2024

  36. [40]

    EIP-779: Hardfork meta: DAO fork

    Casey Detrio. EIP-779: Hardfork meta: DAO fork. Technical Report 779, Ethereum Improvement Proposals, November 2017. Status: Meta

    2017

  37. [41]

    Eip-4973 - account-bound tokens

    TimDaub. Eip-4973 - account-bound tokens. Ethereum Magicians Forum Post, April 2022

    2022

  38. [42]

    Eip-6381: Public non-fungible token emote repository

    Author of the forum post. Eip-6381: Public non-fungible token emote repository. Ethereum Magicians Forum Post, Month of post Year of post

  39. [43]

    Mapping the NFT revolution: market trends, trade networks, and visual features

    Matthieu Nadini, Laura Alessandretti, Flavio Di Giacinto, et al. Mapping the NFT revolution: market trends, trade networks, and visual features. Scientific Reports, 11(1):20902, 2021

    2021

  40. [44]

    Het- erogeneous rarity patterns drive price dynamics in NFT collections

    Amin Mekacher, Alberto Bracci, Matthieu Nadini, Mauro Martino, Laura Alessandretti, Luca Maria Aiello, and Andrea Baronchelli. Het- erogeneous rarity patterns drive price dynamics in NFT collections. Scientific reports, 12(1):13890, 2022

    2022

  41. [45]

    Networks of ethereum non-fungible tokens: A graph-based analysis of the ERC-721 ecosystem

    Simone Casale-Brunet, Paolo Ribeca, Patrick Doyle, and Marco Mat- tavelli. Networks of ethereum non-fungible tokens: A graph-based analysis of the ERC-721 ecosystem. In IEEE International Conference on Blockchain (Blockchain) , pages 188–195. IEEE, 2021

    2021

  42. [46]

    Analyzing erc-1155 adoption: A study of the multi-token ecosystem

    Matteo Loporchio, Damiano Di Francesco Maesa, Anna Bernasconi, and Laura Ricci. Analyzing erc-1155 adoption: A study of the multi-token ecosystem. In International Conference on Complex Networks and Their Applications, pages 385–397. Springer, 2024

    2024

  43. [47]

    Bubble or not: an analysis of ethereum erc721 and erc1155 non- fungible token ecosystem

    Yixiang Tan, Zhiying Wu, Jieli Liu, Jiajing Wu, Ting Chen, and Kaixin Lin. Bubble or not: an analysis of ethereum erc721 and erc1155 non- fungible token ecosystem. In IEEE International Symposium on Circuits and Systems (ISCAS) , pages 1–5. IEEE, 2024

    2024

  44. [48]

    Comparing ethereum fungible and non-fungible tokens: an analysis of transfer networks

    Matteo Loporchio, Damiano Di Francesco Maesa, Anna Bernasconi, and Laura Ricci. Comparing ethereum fungible and non-fungible tokens: an analysis of transfer networks. Applied Network Science , 9(1):72, 2024

    2024

  45. [49]

    The fungibility of non-fungible tokens: A quantitative analysis of ERC-721 metadata

    Sarah Barrington and Nick Merrill. The fungibility of non-fungible tokens: A quantitative analysis of ERC-721 metadata. arXiv preprint arXiv:2209.14517, 2022

    2022 arXiv

  46. [50]

    Are NFTs ready to keep australian artists engaged? arXiv preprint arXiv:2507.06926, 2025

    Ruiqiang Li, Brian Yecies, Qin Wang, Shiping Chen, and Jun Shen. Are NFTs ready to keep australian artists engaged? arXiv preprint arXiv:2507.06926, 2025

    2025 arXiv

  47. [51]

    Demystifying non fungible tokens (NFTs)

    European Commission, Directorate-General for Communications Net- works, Content and Technology. Demystifying non fungible tokens (NFTs). Technical report, European Commission, 2021

    2021

  48. [52]

    Non-fungible token security

    Peter Mell and Dylan Yaga. Non-fungible token security. Technical Report NIST IR 8472, National Institute of Standards and Technology, March 2024

    2024

  49. [53]

    Empowering visual artists with tokenized digital assets with NFTs

    Ruiqiang Li, Brian Yecies, Qin Wang, Shiping Chen, and Jun Shen. Empowering visual artists with tokenized digital assets with NFTs. arXiv preprint arXiv:2409.11790, 2024

    2024 arXiv

  50. [54]

    Towards proxy staking accounts based on NFTs in Ethereum

    Viktor Vala ˇst´ın, Roman Bitarovsk `y, Kristi ´an Koˇst´al, and Ivan Kotuliak. Towards proxy staking accounts based on NFTs in Ethereum. In 2024 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), pages 1–7. IEEE, 2024

    2024

  51. [55]

    ERC-20r and ERC-721r: Reversible transactions on Ethereum

    Kaili Wang, Qinchen Wang, and Dan Boneh. ERC-20r and ERC-721r: Reversible transactions on Ethereum. arXiv preprint arXiv:2208.00543, 2022

    2022 arXiv

  52. [56]

    A secure standard for NFT fractionalization

    Wejdene Haouari and Marios Fokaefs. A secure standard for NFT fractionalization. arXiv preprint arXiv:2409.08190 , 2024

    2024 arXiv

  53. [57]

    Non-fungible tokens (NFTs) in healthcare: a thematic analysis and research agenda

    Khulekani Sibanda, Patrick Ndayizigamiye, and Hossana Twinomurinzi. Non-fungible tokens (NFTs) in healthcare: a thematic analysis and research agenda. Frontiers in Digital Health , 6:1377531, 2024

    2024

  54. [58]

    A review of non-fungible tokens applications in the real-world and metaverse

    Saeed Banaeian Far, Seyed Mojtaba Hosseini Bamakan, Qiang Qu, and Qingshan Jiang. A review of non-fungible tokens applications in the real-world and metaverse. Procedia Computer Science , 214:755–762, 2022

    2022

  55. [59]

    Educational applications of non- fungible token (nft)

    Chih-Hung Wu and Chien-Yu Liu. Educational applications of non- fungible token (nft). Sustainability, 15(1):7, 2022

    2022

  56. [60]

    Use of non- fungible tokens in operations and supply chain management

    Petri Helo, Yuqiuge Hao, and Angappa Gunasekaran. Use of non- fungible tokens in operations and supply chain management. Interna- tional Journal of Production Research , pages 1–23, 2025

    2025

  57. [62]

    NFT smart contract security: Common pitfalls and auditing guidelines

    Olympix. NFT smart contract security: Common pitfalls and auditing guidelines. Medium, October 2024

    2024

  58. [63]

    Popular NFT types explained: ERC-721 vs 721a vs 1155

    Transak Team. Popular NFT types explained: ERC-721 vs 721a vs 1155. Blog Post, February 2024

    2024

  59. [64]

    1155 vs ERC-721 - which is better for NFT standards

    Rejolut. 1155 vs ERC-721 - which is better for NFT standards. Blog Post

  60. [65]

    ERC-6551 standard: Token bound accounts (tba)

    RareSkills. ERC-6551 standard: Token bound accounts (tba). Blog Post

  61. [66]

    EIP 6551 overview — token bounds accounts and its security challenges

    Mundus. EIP 6551 overview — token bounds accounts and its security challenges. Blog Post

  62. [67]

    A complete guide to ERC-6551: Token bound accounts

    GoldRush. A complete guide to ERC-6551: Token bound accounts. Blog Post

  63. [68]

    Eip-4907: Rental NFT, an extension of ERC-721

    Author(s) listed on the EIP page. Eip-4907: Rental NFT, an extension of ERC-721. Technical Report 4907, Ethereum Improvement Proposals, Year of creation. Status: Status of the EIP, e.g., Draft, Review, Final

  64. [70]

    EIP-4675: Token URI JSON Schema

    Author(s) listed on the EIP page. EIP-4675: Token URI JSON Schema. Technical Report EIP-4675, Ethereum Improvement Proposals, Year of creation. Status: Status of the EIP, e.g., Draft, Review, Final

  65. [72]

    EIP- 2981: NFT royalty standard

    Zach Burks, James Morgan, Blaine Malone, and James Seibel. EIP- 2981: NFT royalty standard. Technical Report 2981, Ethereum Im- provement Proposals, September 2020. Status: Final

    2020

  66. [73]

    ‘ERC-2981‘ (NFT royalty standard) implementation

    pcaversaccio. ‘ERC-2981‘ (NFT royalty standard) implementation. GitHub Issue

Pith tools

Reviewed August 5, 2026 · model on record in the stance chip above.