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Paper Citation Record · LEDGER

Pre-trained Large Language Models for Financial Sentiment Analysis

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2401.05215.

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

pith.paper-citation-record.v1
2401.05215 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:12:06.257225Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T06:36:36.496454Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 81aba56d-f41c-49a5-bb68-f73b188628ac · inbound

Event-Aware Sentiment Factors from LLM-Augmented Financial Tweets: A Transparent Framework for Interpretable Quant Trading cites this paper.

Event-Aware Sentiment Factors from LLM-Augmented Financial Tweets: A Transparent Framework for Interpretable Quant Trading Pre-trained Large Language Models for Financial Sentiment Analysis

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-05T22:12:06.257225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T22:12:06.257225Z digest=sha256:dbaa90bb2af467f3b519e64902440b6004df14f641c15c6d92892144109e5c80

Observation cf2b9f92-179c-43a8-a3c1-adf07745262a · inbound

Understanding and Enforcing Weight Disentanglement in Task Arithmetic cites this paper.

Understanding and Enforcing Weight Disentanglement in Task Arithmetic Pre-trained Large Language Models for Financial Sentiment Analysis

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-10T06:36:36.497857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-10T06:35:33.560079Z digest=sha256:47ce8c7a2f2e641314231c94166c9cc4ce4d0a860d859fa0652869850a0ca4e1