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Paper Citation Record · LEDGER

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study

As of 14 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 2 inbound Pith citation observations for arXiv:2501.18158.

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

pith.paper-citation-record.v1
2501.18158 v3

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T00:31:52.854001Z

measured 54 of 54 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:20:10.474294Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-13T17:38:02.425714Z

Reference resolution

52 of 52 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4401e68d-b919-4c73-a663-172281b0254d · outbound

This paper cites A survey on evaluation of large language models.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study A survey on evaluation of large language models

Reference 1

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Observation b152342a-3abb-4ace-983f-c74477d8d7c4 · outbound

This paper cites Recent advances in natural language processing via large pre- trained language models: A survey.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Recent advances in natural language processing via large pre- trained language models: A survey

Reference 2

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Observation 232919b7-15c6-4f27-b8b7-9043aa1c0157 · outbound

This paper cites Fine-tuning large neural language models for biomedical natural language processing.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Fine-tuning large neural language models for biomedical natural language processing

Reference 3

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Source-reported events for the cited work

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Observation a30bb1b2-0b3d-4785-8b6e-c46170e8bfb9 · outbound

This paper cites Visionllm: Large language model is also an open-ended decoder for vision-centric tasks.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Visionllm: Large language model is also an open-ended decoder for vision-centric tasks

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 329bfe3d-41d8-4d55-942b-d262bdd8380b · outbound

This paper cites MiniGPT-4: Enhancing vision-language understanding with advanced large language models.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study MiniGPT-4: Enhancing vision-language understanding with advanced large language models

Reference 5

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Source-reported events for the cited work

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Observation e4abfd5b-e12e-4f0e-8e42-8c01c93b190f · outbound

This paper cites Large language models for code: Security hardening and adversarial testing.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Large language models for code: Security hardening and adversarial testing

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 5334352b-a211-4782-ab60-2f1e02451757 · outbound

This paper cites Lost at C: A user study on the security implications of large language model code assistants.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Lost at C: A user study on the security implications of large language model code assistants

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 40069ba0-0be8-4009-b396-cd55d528be29 · outbound

This paper cites Large language models encode clinical knowledge.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Large language models encode clinical knowledge

Reference 8

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Source-reported events for the cited work

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Observation 8e84a62a-91f7-49c2-86d5-4c0efcc7d1ec · outbound

This paper cites GPT4Graph: Can Large Language Models Understand Graph Structured Data ? An Empirical Evaluation and Benchmarking.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study GPT4Graph: Can Large Language Models Understand Graph Structured Data ? An Empirical Evaluation and Benchmarking

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e6b7572a-5745-44a4-8983-34f8f40a3d16 · outbound

This paper cites Beyond Text: A Deep Dive into Large Language Models' Ability on Understanding Graph Data.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Beyond Text: A Deep Dive into Large Language Models' Ability on Understanding Graph Data

Reference 10

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Source-reported events for the cited work

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Observation ff8926e7-ba66-4215-9b65-bf7e35f217ac · outbound

This paper cites Can language models solve graph problems in natural language? In Advances in Neural Information Processing Systems (NeurIPS), volume 36, pages 30840–30861, 2023.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Can language models solve graph problems in natural language? In Advances in Neural Information Processing Systems (NeurIPS), volume 36, pages 30840–30861, 2023

Reference 11

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Source-reported events for the cited work

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Observation 59ea7f8b-120f-4804-92d1-9a70201a7197 · outbound

This paper cites LLM4DyG: Can large language models solve spatial- temporal problems on dynamic graphs? In ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) , page 4350–4361, 2024.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study LLM4DyG: Can large language models solve spatial- temporal problems on dynamic graphs? In ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) , page 4350–4361, 2024

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 9044d4f4-1d6a-4b6a-954c-b196811f2a9e · outbound

This paper cites BABD: A Bitcoin address behavior dataset for pattern analysis.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study BABD: A Bitcoin address behavior dataset for pattern analysis

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation cffc8535-1b10-4407-a0fd-f019710015c1 · outbound

This paper cites Cryptocurrency in the aftermath: Unveiling the impact of the SVB collapse.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Cryptocurrency in the aftermath: Unveiling the impact of the SVB collapse

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation dd3aef6e-f97e-463b-b74a-bc823c748d01 · outbound

This paper cites Miracle or mirage? a measurement study of NFT rug pulls.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Miracle or mirage? a measurement study of NFT rug pulls

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 57ac7ca7-4fb3-4b36-bd25-3faa443a8a8f · outbound

This paper cites An Empirical Study on Snapshot DAOs.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study An Empirical Study on Snapshot DAOs

Reference 16

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Source-reported events for the cited work

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Observation e24c0a71-1156-44c6-9b95-54f6e20edfc5 · outbound

This paper cites Understanding Ethereum via graph analysis.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Understanding Ethereum via graph analysis

Reference 17

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Source-reported events for the cited work

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Observation b5687b05-4608-4845-ac62-b3796f340d96 · outbound

This paper cites Tracking counterfeit cryptocurrency end-to-end.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Tracking counterfeit cryptocurrency end-to-end

Reference 18

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Source-reported events for the cited work

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Observation b6b0e6fd-9dd3-4fee-9660-5d7eabd1c08c · outbound

This paper cites An empirical analysis of pool hopping behavior in the Bitcoin blockchain.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study An empirical analysis of pool hopping behavior in the Bitcoin blockchain

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation cb986ed5-3c08-4e7c-a6bf-a6a0a8aff29b · outbound

This paper cites A study on nine years of Bitcoin transactions: Understanding real-world behaviors of bitcoin miners and users.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study A study on nine years of Bitcoin transactions: Understanding real-world behaviors of bitcoin miners and users

Reference 20

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Source-reported events for the cited work

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Observation 62944965-e55e-4b65-b94d-913dcc0ff5aa · outbound

This paper cites Double and nothing: Understanding and detecting cryptocurrency giveaway scams.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Double and nothing: Understanding and detecting cryptocurrency giveaway scams

Reference 21

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation e39d5b38-ab4b-4008-9aa1-df9aa5867f78 · outbound

This paper cites TxPhishScope: Towards detecting and understanding transaction-based phishing on Ethereum.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study TxPhishScope: Towards detecting and understanding transaction-based phishing on Ethereum

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 8036e110-38e7-4fd0-9489-73b742df4bc3 · outbound

This paper cites Watch your back: Identifying cybercrime financial relationships in Bitcoin through back-and-forth exploration.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Watch your back: Identifying cybercrime financial relationships in Bitcoin through back-and-forth exploration

Reference 23

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Source-reported events for the cited work

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Observation 8a0f63b8-b246-4118-b62a-eb4e24f19aad · outbound

This paper cites Toward understanding asset flows in crypto money laundering through the lenses of ethereum heists.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Toward understanding asset flows in crypto money laundering through the lenses of ethereum heists

Reference 24

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Observation a026afb6-7780-4a75-b94b-8b2cbe0bf0e3 · outbound

This paper cites Do cryptocurrency exchanges fake trading volumes? an empirical analysis of wash trading based on data mining.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Do cryptocurrency exchanges fake trading volumes? an empirical analysis of wash trading based on data mining

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 358698b4-ccc8-4c2d-bc42-ca9e4b3860f2 · outbound

This paper cites Dissecting Bitcoin blockchain: Empirical analysis of Bitcoin network (2009–2020).

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Dissecting Bitcoin blockchain: Empirical analysis of Bitcoin network (2009–2020)

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 7059030a-8ebe-4777-aecb-c49994f340c4 · outbound

This paper cites Cryptocurrencies activity as a complex network: Analysis of transactions graphs.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Cryptocurrencies activity as a complex network: Analysis of transactions graphs

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 388cdb09-3690-44c9-b284-57da1ca262ef · outbound

This paper cites Complex network analysis of the Bitcoin transaction network.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Complex network analysis of the Bitcoin transaction network

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 8fc51806-2130-486a-9fab-ce9c99d722eb · outbound

This paper cites Graph structure and statistical properties of Ethereum transaction relationships.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Graph structure and statistical properties of Ethereum transaction relationships

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-10T00:31:53.303327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation ccf0a2ac-fb2b-42fb-b6c4-a575bdc8f6fa · outbound

This paper cites DenseFlow: Spotting cryptocurrency money laundering in Ethereum transaction graphs.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study DenseFlow: Spotting cryptocurrency money laundering in Ethereum transaction graphs

Reference 30

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raw_fallback, observed 2026-08-10T00:31:53.286767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 9cf5fa91-ae53-4dd2-a062-a24b78d7d009 · outbound

This paper cites To- wards malicious address identification in Bitcoin.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study To- wards malicious address identification in Bitcoin

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 597eaebb-6091-47c1-b4d2-7eb30a46bdb7 · outbound

This paper cites Mixers detection in Bitcoin network: a step towards detecting money laundering 13 in crypto-currencies.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Mixers detection in Bitcoin network: a step towards detecting money laundering 13 in crypto-currencies

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 4dfa67d0-448c-4c49-b3b8-4b59ae11d9b0 · outbound

This paper cites Improving cryptocurrency crime detection: Coinjoin community detec- tion approach.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Improving cryptocurrency crime detection: Coinjoin community detec- tion approach

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation ab3fb540-f968-49b2-a0f7-9a70fb4dc5c9 · outbound

This paper cites Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-10T00:31:52.766172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T00:31:52.766172Z digest=sha256:825a15dd3c4915a73d1dd008c63e33d2211d92538fdbccc7b04b3548c6d4b50f

Observation 6e097529-83c3-4cda-8106-f60e23726ede · outbound

This paper cites Leveraging subgraph structure for exploration and analysis of Bitcoin address.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Leveraging subgraph structure for exploration and analysis of Bitcoin address

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T00:31:53.225153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T00:31:52.771326Z digest=sha256:45b9425d900ec1339c0e69f92d9191fa13ac9dbcbc55e8dd2739e1eadc6c9ed1

Observation 41fedaf1-f1b2-42d0-9bec-930925c3bdf0 · outbound

This paper cites Blockchain Large Language Models.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Blockchain Large Language Models

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-10T00:31:52.776112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T00:31:52.776112Z digest=sha256:211ff1b84044d9cd2b0e12fa357627c92c80494f47d91c2f3c3204f22292815a

Observation 641e74f1-2519-45b1-afa2-9fbc05f1caa4 · outbound

This paper cites A survey of graph meets large language model: Progress and future directions.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study A survey of graph meets large language model: Progress and future directions

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T00:31:53.210117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T00:31:52.781564Z digest=sha256:a1fdaed0a83d461a258f2f5cb6f74e499e077dbce7c642ad5d618446587cf582

Observation 47ae8435-364b-43e3-8e56-f9f085525447 · outbound

This paper cites Predicting nft classification with GNN: A recommender system for web3 assets.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Predicting nft classification with GNN: A recommender system for web3 assets

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T00:31:53.194636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T00:31:52.786268Z digest=sha256:cf48419904a33149788a217bad328c44a1b4723e065cdfb91a36fec709288b78

Observation 9d90a43d-bc75-4380-981d-4807bada3b6f · outbound

This paper cites Grapharena: Evaluating and exploring large language models on graph computation.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Grapharena: Evaluating and exploring large language models on graph computation

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T00:31:53.179909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T00:31:52.790893Z digest=sha256:ee1b4381abf46700e80e665deb3125bd5b9652ab183c6df0afa482845d1abe3d

Observation b083a275-8bc2-454f-99da-4ffe9a0c5cd1 · outbound

This paper cites Table meets LLM: Can large language models understand structured table data? a benchmark and empirical study.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Table meets LLM: Can large language models understand structured table data? a benchmark and empirical study

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T00:31:53.165436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T00:31:52.795639Z digest=sha256:d446a30891a3cb0f40f6422b032cbe2ddc391ee3c651b28be6c3137796a4062a

Observation 9501a231-ff43-42f2-9336-0e065c450ca6 · outbound

This paper cites StructGPT: A general framework for large language model to reason over structured data.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study StructGPT: A general framework for large language model to reason over structured data

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T00:31:53.150776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T00:31:52.800095Z digest=sha256:b8dcd94e623218692efc4020ca9bdf745cbac9aaf1f55f50308d70290441bddd

Observation 2ba99700-5eae-4747-aba4-62b57c6e03f4 · outbound

This paper cites Which modality should I use - text, motif, or image? : Understanding graphs with large language models.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Which modality should I use - text, motif, or image? : Understanding graphs with large language models

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T00:31:53.136379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T00:31:52.804835Z digest=sha256:b1ad3eb547d68d1e573c559c6d9253d4571b704d299bfa3625f96d202066bdf2

Observation b5f8d3b8-6237-44c7-8288-8a6fae8161fa · outbound

This paper cites Exploring the potential of large language models (LLMs) in learning on graphs.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Exploring the potential of large language models (LLMs) in learning on graphs

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T00:31:53.121427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T00:31:52.809604Z digest=sha256:80444104253d71b6794b10f9d38c331953679ce9c22a2d9ce73cd9feddbe7a86

Observation d0154ad8-68e2-436d-834f-d200a71b6e7e · outbound

This paper cites Label-free node classification on graphs with large language models (LLMs).

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Label-free node classification on graphs with large language models (LLMs)

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T00:31:53.106623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T00:31:52.814393Z digest=sha256:56dba9aada8a98c1360c5ef6ef23fee11dd79501242dd0e1a31d603d40b9f0cf

Observation 84a21db5-f975-4fd7-9692-47f303138bc3 · outbound

This paper cites Head-to-tail: How knowledgeable are large language models (LLMs)? a.k.a.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Head-to-tail: How knowledgeable are large language models (LLMs)? a.k.a

Reference 45

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verified fuzzy
raw_fallback, observed 2026-08-10T00:31:53.091090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T00:31:52.819319Z digest=sha256:ce5bd24638494f4e24bd5d0a6d6c2fa22308ddf928f8ee2e7cc7b23a4c3a61ca

Observation c91a23fb-8928-45b9-a274-b03cdf1f0ada · outbound

This paper cites GPT-4 Technical Report.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study GPT-4 Technical Report

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-10T00:31:52.824473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T00:31:52.824473Z digest=sha256:7b4b4b8b3a10d9b1d5fe780513f751dd7c8179573c092a87642676179f88794e

Observation 4a5640b8-3e48-457d-9c27-7af09f47024c · outbound

This paper cites Large language models on graphs: A comprehensive survey.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Large language models on graphs: A comprehensive survey

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T00:31:53.074545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T00:31:52.829566Z digest=sha256:b611135a040cf311d19f300ad128acf2785d2b52fe2b2e1b603026f07c830c27

Observation 79e40494-8b9e-40a8-b53b-d211cd7af571 · outbound

This paper cites Graph summarization with controlled utility loss.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Graph summarization with controlled utility loss

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T00:31:53.057545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T00:31:52.834180Z digest=sha256:fa0415117e0984bbf424e9dc3cdb84b3dc752515758ecf03633b7a63e09dc6ac

Observation 60d15cd2-f7fc-4bc8-8625-7a2c053681e1 · outbound

This paper cites Personalized graph summarization: formulation, scalable algorithms, and applications.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Personalized graph summarization: formulation, scalable algorithms, and applications

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T00:31:53.040465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T00:31:52.838950Z digest=sha256:059e5aa192d0e014d66d0b22309ebbf7489ea47e9d950831a8ad4df2cb62d8e8

Observation 7368c3ad-bdba-4a63-b8e3-0f35a71c74b4 · outbound

This paper cites Ssumm: Sparse summarization of massive graphs.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Ssumm: Sparse summarization of massive graphs

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T00:31:53.023736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T00:31:52.843867Z digest=sha256:9ce5d3a170b9da6ef79f268e54a183900d4ecdf26533385b51f8fc17f35005aa

Observation 1ff76951-43ca-4ee8-90f0-96d1c4a1e7be · outbound

This paper cites An optimized lossless graph summarization for large-scale graphs.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study An optimized lossless graph summarization for large-scale graphs

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T00:31:53.008067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T00:31:52.849217Z digest=sha256:79dc7382cc3f6177acb17bc83d380dff3d2290a48492aceed7550e662593b36d

Observation 745ed3ca-0861-462c-bb0b-af49e7dca964 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study Chain-of-thought prompting elicits reasoning in large language models

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T00:31:52.991402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-10T00:31:52.854001Z digest=sha256:ba6abbf85a2154e076b5d6054b90e966c69fa5d4673d50e28ec7996ff35bcafa

Pith citing papers

Observation b2ab968e-cbc6-4faa-b48f-a9643c4d1359 · inbound

Talking Transactions: Decentralized Communication through Ethereum Input Data Messages (IDMs) cites this paper.

Talking Transactions: Decentralized Communication through Ethereum Input Data Messages (IDMs) Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study

Reference 33

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unresolved
no resolver link, observed 2026-08-07T12:20:10.474294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:20:10.474294Z digest=sha256:87937adb2cd87af4ee0ec6a4ddf4a21c32494fa171d47fec25d755bdea7bc992

Observation dfd43d18-b854-4264-a12b-bc06ea4326da · inbound

SoK: Blockchain Agent-to-Agent Payments cites this paper.

SoK: Blockchain Agent-to-Agent Payments Large Language Models for Cryptocurrency Transaction Analysis: A Bitcoin Case Study

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-13T17:38:02.427962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-13T17:37:50.514729Z digest=sha256:5d3f512d38ce841606b8c1cc9fe38dfc5789202f56f8bc90a6421d2559a2cf82