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Paper Citation Record · LEDGER

A Survey of Large Language Models in Finance (FinLLMs)

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2402.02315.

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

pith.paper-citation-record.v1
2402.02315 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:50:40.762656Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

14
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a6dafca1-3eef-4887-b8f0-a4254de01c12 · inbound

Assessing the Capabilities and Limitations of FinGPT Model in Financial NLP Applications cites this paper.

Assessing the Capabilities and Limitations of FinGPT Model in Financial NLP Applications A Survey of Large Language Models in Finance (FinLLMs)

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-06T19:50:40.762656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:50:40.762656Z digest=sha256:2127d0fd51fc4647ece57f5e073a4f5ab2839d8e9595940acbfb71a0cd235837

Observation 2907f404-8369-4dcd-95ac-75b460a17657 · inbound

QRAFTI: An Agentic Framework for Empirical Research in Quantitative Finance cites this paper.

QRAFTI: An Agentic Framework for Empirical Research in Quantitative Finance A Survey of Large Language Models in Finance (FinLLMs)

Reference 64

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:46:02.726520Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-05-10T03:06:14.794251Z digest=sha256:061a2a19e54548beb37f93a3ca2c82027569ba0f96dd4ec8db585b9ef27c1098

Observation 1375aec8-9e7d-4a01-998e-3f6dde01540f · inbound

Explainable AML Triage with LLMs: Evidence Retrieval and Counterfactual Checks cites this paper.

Explainable AML Triage with LLMs: Evidence Retrieval and Counterfactual Checks A Survey of Large Language Models in Finance (FinLLMs)

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-15T07:35:13.160496Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-15T07:34:57.278796Z digest=sha256:7bd81562527d5a2699f1d1653fc9642904270c325553496441bcbb057679fce6

Observation 9738f2d2-5076-4948-b1c0-b3fdef9b9c07 · inbound

Trustworthy AI Suffers from Invariance Conflicts and Causality is The Solution cites this paper.

Trustworthy AI Suffers from Invariance Conflicts and Causality is The Solution A Survey of Large Language Models in Finance (FinLLMs)

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-09T05:45:21.153981Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-05-08T19:36:52.668048Z digest=sha256:9ac957c7754641df645f66e079264f73da59ef73eb656810acf61609a4db8675

Observation ee48d1b5-8d82-45fb-beb9-c1e2a0364219 · inbound

MadEvolve: Evolutionary Optimization of Trading Systems with Large Language Models cites this paper.

MadEvolve: Evolutionary Optimization of Trading Systems with Large Language Models A Survey of Large Language Models in Finance (FinLLMs)

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:25:23.334778Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-25T05:24:05.098181Z digest=sha256:6ba1a84cc70c873af7924549e24c864b10446f20218b39ee6aad07bef9cbc7a6

Observation 5f5ff206-c76d-425e-b6dd-7f144cb4a123 · inbound

Beyond Agent Architecture: Execution Assumptions and Reproducibility in LLM-Based Trading Systems cites this paper.

Beyond Agent Architecture: Execution Assumptions and Reproducibility in LLM-Based Trading Systems A Survey of Large Language Models in Finance (FinLLMs)

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-07-02T21:37:25.615618Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-06-27T19:35:11.289439Z digest=sha256:56b60599fff5be8bc84c2c21f4d272b6a6b5c615339e38b212b48c601505f504

Observation b6db1e29-a689-42d0-a76d-03d5f0054000 · inbound

MetaPS: Adaptive Programmatic Strategy Selection for Market Agents cites this paper.

MetaPS: Adaptive Programmatic Strategy Selection for Market Agents A Survey of Large Language Models in Finance (FinLLMs)

Reference 171

Resolution
verified exact
arxiv_id, observed 2026-07-04T08:39:42.655904Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-06-26T11:06:28.690956Z digest=sha256:48fdb18f64234dfe6a9ada4368005c8ef73a8feca1ce06107e35a22fbdbc67eb

Observation 1bb49167-cfb2-4ed8-b7f6-6267b90d203f · inbound

What LLMs explain is not what they believe: Evaluating explanation sufficiency under models' own input beliefs cites this paper.

What LLMs explain is not what they believe: Evaluating explanation sufficiency under models' own input beliefs A Survey of Large Language Models in Finance (FinLLMs)

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-07-01T16:25:50.082486Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-06-30T00:38:21.949283Z digest=sha256:21d9d4d353b79465f638ee4968df67b20a09b32ac744004d2a60ad26a6d815e1

Observation f10b9fdc-4c41-4f26-9d81-b7b9f8565c0a · inbound

TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis cites this paper.

TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis A Survey of Large Language Models in Finance (FinLLMs)

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-01T11:45:21.240451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T11:45:21.240451Z digest=sha256:5b5d14077a5b77107fab3724ba8faff96cd36336b8fcc01cee87cf38fd04623f