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Paper Citation Record · LEDGER

FinLLMs: A Framework for Financial Reasoning Dataset Generation with Large Language Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2401.10744.

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

pith.paper-citation-record.v1
2401.10744 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:27:50.037756Z

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

1
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 cc5701c9-e022-4f44-91c4-62ebc5f5da33 · inbound

Enhancing LLMs' Reasoning-Intensive Multimedia Search Capabilities through Fine-Tuning and Reinforcement Learning cites this paper.

Enhancing LLMs' Reasoning-Intensive Multimedia Search Capabilities through Fine-Tuning and Reinforcement Learning FinLLMs: A Framework for Financial Reasoning Dataset Generation with Large Language Models

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T14:27:50.037756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:27:50.037756Z digest=sha256:71e6c6e92190dcab7681b4f30939a93a6addd31f8cef06a903ac59aa714eca81

Observation 208ce99b-2e60-4612-9b81-7d5f48aca265 · inbound

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models cites this paper.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models FinLLMs: A Framework for Financial Reasoning Dataset Generation with Large Language Models

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T05:20:04.675057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:20:04.675057Z digest=sha256:a99df4f8e9dde1bdc7f0da12d21b3e6640b97d9a9c766b7082791f5427fc1e31

Observation 78a352f2-7fcd-49e9-b0b6-788e5ab663fa · inbound

CF-RAG: A Dataset and Method for Carbon Footprint QA Using Retrieval-Augmented Generation cites this paper.

CF-RAG: A Dataset and Method for Carbon Footprint QA Using Retrieval-Augmented Generation FinLLMs: A Framework for Financial Reasoning Dataset Generation with Large Language Models

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-06T04:30:49.596932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T04:30:49.596932Z digest=sha256:3579de49b47c3cc89140c1944c08faaf984a05da26ed94e075b4993d92e9e32a

Observation e98fad0e-fb33-40f1-a130-94f6301c14b9 · inbound

EmbGen: Teaching with Reassembled Corpora cites this paper.

EmbGen: Teaching with Reassembled Corpora FinLLMs: A Framework for Financial Reasoning Dataset Generation with Large Language Models

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-20T06:38:05.513053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-20T06:34:39.739666Z digest=sha256:c9fba5e6cae51b87ee2dd485ae4c26b72544e2d45fa2d84866e91688fe965a2a