Paper Citation Record · LEDGER

Financial Named Entity Recognition: How Far Can LLM Go?

As of 13 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2501.02237.

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

pith.paper-citation-record.v1
2501.02237 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:16:29.481406Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

13 of 13 outbound references displayed

verified exact0
verified fuzzy6
unresolved7
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a9ca1c8f-4594-4439-bb7f-8199cd1b2591 · outbound

This paper cites The Llama 3 Herd of Models.

Financial Named Entity Recognition: How Far Can LLM Go? The Llama 3 Herd of Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T22:16:29.452714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aac7beaa-61d1-468e-8332-eaf763f8a0b9 · outbound

This paper cites https://ai.google.

Financial Named Entity Recognition: How Far Can LLM Go? https://ai.google

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:16:29.605998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2acf2c02-eab8-4a6d-9a5e-6b66370efd8f · outbound

This paper cites Are ChatGPT and GPT-4 General-Purpose Solvers for Financial Text Analytics? A Study on Several Typical Tasks.

Financial Named Entity Recognition: How Far Can LLM Go? Are ChatGPT and GPT-4 General-Purpose Solvers for Financial Text Analytics? A Study on Several Typical Tasks

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T22:16:29.459707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a811d8b4-2269-4ec3-b6aa-ad7fde78b6c3 · outbound

This paper cites https://chat.openai.com.

Financial Named Entity Recognition: How Far Can LLM Go? https://chat.openai.com

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:16:29.595961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e87d68a4-3658-43c0-be41-e06d82989d51 · outbound

This paper cites https://platform.

Financial Named Entity Recognition: How Far Can LLM Go? https://platform

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:16:29.585731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8105e5b9-0f25-435b-ae38-822b8e2551a8 · outbound

This paper cites Large Language Models Meet NLP: A Survey.

Financial Named Entity Recognition: How Far Can LLM Go? Large Language Models Meet NLP: A Survey

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T22:16:29.473263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2abd2fd-0ce9-40ad-84fd-724ce92834e7 · outbound

This paper cites In Pro- ceedings of the Australasian Language Technology Association Workshop 2015, pages 84–90.

Financial Named Entity Recognition: How Far Can LLM Go? In Pro- ceedings of the Australasian Language Technology Association Workshop 2015, pages 84–90

Reference 2015

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:16:29.626541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a26b6515-491b-460e-861a-c4ae68862bcd · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Financial Named Entity Recognition: How Far Can LLM Go? BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-10T22:16:29.444405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8a8bdca-8fff-4a0a-922e-b158c2494fc1 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Financial Named Entity Recognition: How Far Can LLM Go? RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-10T22:16:29.463424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e390a0e-071c-4dc2-bf0e-f0b0e0232eeb · outbound

This paper cites In Proceedings of the 2020 con- ference on empirical methods in natural language processing: system demonstrations, pages 38–45.

Financial Named Entity Recognition: How Far Can LLM Go? In Proceedings of the 2020 con- ference on empirical methods in natural language processing: system demonstrations, pages 38–45

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:16:29.574733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 86972085-3bca-4dba-bef7-3091d73162f0 · outbound

This paper cites A Survey on In-context Learning.

Financial Named Entity Recognition: How Far Can LLM Go? A Survey on In-context Learning

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-10T22:16:29.448770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 346f7243-2274-4a72-b7c2-adca7fe02451 · outbound

This paper cites FiNER-ORD: Financial Named Entity Recognition Open Research Dataset.

Financial Named Entity Recognition: How Far Can LLM Go? FiNER-ORD: Financial Named Entity Recognition Open Research Dataset

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-10T22:16:29.477026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6de1bf71-ffa4-40f5-a5dc-aebf43285f1d · outbound

This paper cites https:// deepinfra.com/models.

Financial Named Entity Recognition: How Far Can LLM Go? https:// deepinfra.com/models

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:16:29.615866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Pith citing papers

No inbound Pith citation observations are available.