Paper Citation Record · LEDGER

A Study of Large Language Models for Patient Information Extraction: Model Architecture, Fine-Tuning Strategy, and Multi-task Instruction Tuning

As of 5 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2509.04753.

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

pith.paper-citation-record.v1
2509.04753 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T06:01:09.976510Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+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

15 of 15 outbound references displayed

verified exact1
verified fuzzy10
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8cec6ebb-9e2c-4cf3-954c-e0d9c2b9bf65 · outbound

This paper cites Wells, Jr.

A Study of Large Language Models for Patient Information Extraction: Model Architecture, Fine-Tuning Strategy, and Multi-task Instruction Tuning Wells, Jr

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:01:10.104801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 71229233-fb5c-4566-a35b-e8c7f9b1a27e · outbound

This paper cites an unresolved cited work.

A Study of Large Language Models for Patient Information Extraction: Model Architecture, Fine-Tuning Strategy, and Multi-task Instruction Tuning Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-05T06:01:10.075144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 360539f7-3bbf-4ae1-8df8-6d83a671718f · outbound

This paper cites an unresolved cited work.

A Study of Large Language Models for Patient Information Extraction: Model Architecture, Fine-Tuning Strategy, and Multi-task Instruction Tuning Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-05T06:01:10.068240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 278fec12-be05-44d2-8977-9eba69a23b2c · outbound

This paper cites severe headache.

A Study of Large Language Models for Patient Information Extraction: Model Architecture, Fine-Tuning Strategy, and Multi-task Instruction Tuning severe headache

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:01:10.061549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a53dc765-0ae7-48ce-91a2-d2053fe1bc29 · outbound

This paper cites All prompt-based PEFT was conducted within NeMo.

A Study of Large Language Models for Patient Information Extraction: Model Architecture, Fine-Tuning Strategy, and Multi-task Instruction Tuning All prompt-based PEFT was conducted within NeMo

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:01:10.082772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 738fe204-91c4-4767-ab82-e96dffe8b4d5 · outbound

This paper cites Testing and evaluation of health care applications of large language models: A systematic review.

A Study of Large Language Models for Patient Information Extraction: Model Architecture, Fine-Tuning Strategy, and Multi-task Instruction Tuning Testing and evaluation of health care applications of large language models: A systematic review

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T06:01:09.962249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea87c95f-4aec-42d7-8ac5-e9f385093629 · outbound

This paper cites Clinical named entity recognition and relation extraction using natural language processing of medical free text: A systematic review.

A Study of Large Language Models for Patient Information Extraction: Model Architecture, Fine-Tuning Strategy, and Multi-task Instruction Tuning Clinical named entity recognition and relation extraction using natural language processing of medical free text: A systematic review

Reference 12

Resolution: verified exact; doi, observed 2026-08-05T06:01:09.998548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 95f63ceb-a630-46c8-a68e-c8f22feb10b3 · outbound

This paper cites Identifying social determinants of health from clinical narratives: A study of performance, documentation ratio, and potential bias.

A Study of Large Language Models for Patient Information Extraction: Model Architecture, Fine-Tuning Strategy, and Multi-task Instruction Tuning Identifying social determinants of health from clinical narratives: A study of performance, documentation ratio, and potential bias

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:01:10.012955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5abb4b9e-dd78-4b51-850e-ce8825a84d9a · outbound

This paper cites an unresolved cited work.

A Study of Large Language Models for Patient Information Extraction: Model Architecture, Fine-Tuning Strategy, and Multi-task Instruction Tuning Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-05T06:01:10.097636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 78c41a51-4313-4fc7-86cd-e22fb642f8b4 · outbound

This paper cites find the drug events including names, brand names and collective names.

A Study of Large Language Models for Patient Information Extraction: Model Architecture, Fine-Tuning Strategy, and Multi-task Instruction Tuning find the drug events including names, brand names and collective names

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:01:10.090408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f97ea39a-124d-4b4e-bcd8-013ac8671566 · outbound

This paper cites BioBERT: a pre-trained biomedical language representation model for biomedical text mining.

A Study of Large Language Models for Patient Information Extraction: Model Architecture, Fine-Tuning Strategy, and Multi-task Instruction Tuning BioBERT: a pre-trained biomedical language representation model for biomedical text mining

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:01:10.046730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 66366265-38c5-4525-801a-b6ab6cbcd5a0 · outbound

This paper cites A large language model for electronic health records.

A Study of Large Language Models for Patient Information Extraction: Model Architecture, Fine-Tuning Strategy, and Multi-task Instruction Tuning A large language model for electronic health records

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:01:10.038693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1f53047b-2c51-4bcd-ace0-276768db1f94 · outbound

This paper cites Contextualized medication information extraction using Transformer-based deep learning architectures.

A Study of Large Language Models for Patient Information Extraction: Model Architecture, Fine-Tuning Strategy, and Multi-task Instruction Tuning Contextualized medication information extraction using Transformer-based deep learning architectures

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:01:10.022430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e11079b9-ba11-4545-a891-2a70f623cb03 · outbound

This paper cites 2010 i2b2/VA challenge on concepts, assertions, and relations in clinical text.

A Study of Large Language Models for Patient Information Extraction: Model Architecture, Fine-Tuning Strategy, and Multi-task Instruction Tuning 2010 i2b2/VA challenge on concepts, assertions, and relations in clinical text

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:01:10.054516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2c2e2fcc-96a2-41fc-a3c0-cc6614499c50 · outbound

This paper cites A study of generative large language model for medical research and healthcare.

A Study of Large Language Models for Patient Information Extraction: Model Architecture, Fine-Tuning Strategy, and Multi-task Instruction Tuning A study of generative large language model for medical research and healthcare

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:01:10.030520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Pith citing papers

No inbound Pith citation observations are available.