Paper Citation Record · LEDGER

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations

As of 21 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2412.04254.

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

pith.paper-citation-record.v1
2412.04254 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T21:38:08.055134Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

43 of 43 outbound references displayed

verified exact7
verified fuzzy14
unresolved22
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 54b84679-3b84-41f1-84c9-ed75fa8b1e03 · outbound

This paper cites MedInsight: A Multi-Source Context Augmentation Framework for Generating Patient-Centric Medical Responses using Large Language Models.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations MedInsight: A Multi-Source Context Augmentation Framework for Generating Patient-Centric Medical Responses using Large Language Models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T21:38:07.924350Z

Source-reported events for the cited work

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Observation 69ccd8db-ac2c-4645-ac18-6e783a4acd6c · outbound

This paper cites Retrieval-Augmented Generation for AI-Generated Content: A Survey.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Retrieval-Augmented Generation for AI-Generated Content: A Survey

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T21:38:07.928260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e3c02f6-3bdc-4d2e-b294-ee62c0bcbbd8 · outbound

This paper cites Remembering what the doctor said: organization and adults’ memory for medical information,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Remembering what the doctor said: organization and adults’ memory for medical information,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:38:08.441972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation baf91ca3-1f4e-42e7-8fb3-75ee8b387ac1 · outbound

This paper cites Patient information recall in a rheumatology clinic,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Patient information recall in a rheumatology clinic,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:38:08.432195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cfa30443-0aa4-4ef4-b2bb-d3dca1971414 · outbound

This paper cites Burnout and doctors: prevalence, prevention and interven- tion,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Burnout and doctors: prevalence, prevention and interven- tion,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:38:08.421856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3f4cc1e9-c28a-46be-b275-a05dbb95cb9e · outbound

This paper cites User-Driven Research of Medical Note Generation Software.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations User-Driven Research of Medical Note Generation Software

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-11T21:38:08.216538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 69a98229-6be5-4548-9e80-83418ef96b3f · outbound

This paper cites A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T21:38:07.945431Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e260abb-1832-4294-817b-9c9c511e7655 · outbound

This paper cites An empirical study of clinical note generation from doctor-patient encounters,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations An empirical study of clinical note generation from doctor-patient encounters,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:38:08.412790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4db8822c-c235-4ffe-be6a-e9da253b230c · outbound

This paper cites Leveraging Pretrained Models for Automatic Summarization of Doctor-Patient Conversations.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Leveraging Pretrained Models for Automatic Summarization of Doctor-Patient Conversations

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-11T21:38:08.196675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d4a5e1de-1bba-4ee8-8263-3b860c03ae9a · outbound

This paper cites WangLab at MEDIQA-Chat 2023: Clinical Note Generation from Doctor-Patient Conversations using Large Language Models.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations WangLab at MEDIQA-Chat 2023: Clinical Note Generation from Doctor-Patient Conversations using Large Language Models

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-11T21:38:08.184334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 940151a8-c6bc-4682-887c-ea9bd336a2ec · outbound

This paper cites Language mod- els are few-shot learners,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Language mod- els are few-shot learners,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T21:38:07.958023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2fe7c28a-b22e-462f-9164-87e78ebccfa0 · outbound

This paper cites Towards an automated soap note: classi- fying utterances from medical conversations,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Towards an automated soap note: classi- fying utterances from medical conversations,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:38:08.397524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 36f2800e-e1ca-4439-92c6-c066aef35729 · outbound

This paper cites Allocation of physician time in ambulatory practice: a time and motion study in 4 specialties,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Allocation of physician time in ambulatory practice: a time and motion study in 4 specialties,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:38:08.387722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5eccfadf-d502-4aa8-96b4-767071d32bdc · outbound

This paper cites The problem oriented record as a basic tool in medical education, patient care and clinical research.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations The problem oriented record as a basic tool in medical education, patient care and clinical research

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:38:08.377673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 63961b7f-4ff3-49d0-9d09-08267af8b055 · outbound

This paper cites Attention is all you need,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Attention is all you need,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T21:38:07.969508Z

Source-reported events for the cited work

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Observation 797c4f57-6c25-4043-8020-a619190b1852 · outbound

This paper cites Recent advances in natural language processing via large pre-trained language models: A survey,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Recent advances in natural language processing via large pre-trained language models: A survey,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T21:38:07.972396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca536a4f-61a6-46cf-b964-9d2eb9e6c232 · outbound

This paper cites Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T21:38:07.975215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d88be82-de31-4953-abc1-d87b19acdd53 · outbound

This paper cites Overcoming catastrophic forgetting in neural networks,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Overcoming catastrophic forgetting in neural networks,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T21:38:07.978488Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4495a3eb-8b37-4725-b582-cca2a7b040e4 · outbound

This paper cites Retrieval- augmented generation for knowledge-intensive nlp tasks,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Retrieval- augmented generation for knowledge-intensive nlp tasks,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T21:38:07.981241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d989808d-d705-4970-b839-abbc6ff825bf · outbound

This paper cites Parameter-efficient transfer learning for nlp,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Parameter-efficient transfer learning for nlp,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T21:38:07.984310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 72bec3bd-be37-4e0e-92c6-ef35477257ed · outbound

This paper cites The Power of Scale for Parameter-Efficient Prompt Tuning.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations The Power of Scale for Parameter-Efficient Prompt Tuning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T21:38:07.987220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c57f8b6a-1c00-40c9-afee-22af9efc0d07 · outbound

This paper cites DyLoRA: Parameter Efficient Tuning of Pre-trained Models using Dynamic Search-Free Low-Rank Adaptation.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations DyLoRA: Parameter Efficient Tuning of Pre-trained Models using Dynamic Search-Free Low-Rank Adaptation

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T21:38:07.990347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 594f9073-1d34-4b07-87c0-056e7b8db6d9 · outbound

This paper cites Qlora: Efficient finetuning of quantized llms,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Qlora: Efficient finetuning of quantized llms,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-11T21:38:07.993464Z

Source-reported events for the cited work

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Observation 3b87e3a8-17d3-47a3-bf6c-923ac504d0c8 · outbound

This paper cites Abstractive dialogue summarization with sentence-gated modeling optimized by dialogue acts,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Abstractive dialogue summarization with sentence-gated modeling optimized by dialogue acts,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:38:08.333226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 25fdfdd9-1ea2-4250-a985-c7da0ce302be · outbound

This paper cites Keep meeting summaries on topic: Abstractive multi-modal meeting summarization,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Keep meeting summaries on topic: Abstractive multi-modal meeting summarization,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:38:08.324066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fd3200dd-d097-4f27-87ec-357916ea2908 · outbound

This paper cites Learning to Summarize Radiology Findings.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Learning to Summarize Radiology Findings

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-08-11T21:38:08.148109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9801d650-b719-45e5-bcb9-1d3063e40edd · outbound

This paper cites An automated medical scribe for documenting clinical encounters,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations An automated medical scribe for documenting clinical encounters,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:38:08.314906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9e0d5a59-542d-4363-afbf-b507e15a9540 · outbound

This paper cites Generating medical reports from patient-doctor conversations using sequence-to-sequence models,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Generating medical reports from patient-doctor conversations using sequence-to-sequence models,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:38:08.305688Z

Source-reported events for the cited work

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Observation 723f0c2f-f288-42ef-8788-786c2374e60c · outbound

This paper cites Generating SOAP Notes from Doctor-Patient Conversations Using Modular Summarization Techniques.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Generating SOAP Notes from Doctor-Patient Conversations Using Modular Summarization Techniques

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-08-11T21:38:08.135829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8997d9e4-daf1-466b-a332-87217c0dabeb · outbound

This paper cites Generating more faithful and consistent soap notes using attribute-specific parameters,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Generating more faithful and consistent soap notes using attribute-specific parameters,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:38:08.296695Z

Source-reported events for the cited work

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Observation cbe578e3-6769-4abc-9c94-fdfafdcf9eb6 · outbound

This paper cites Language models are unsupervised multitask learners,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Language models are unsupervised multitask learners,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T21:38:08.017757Z

Source-reported events for the cited work

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Observation 8faf5fd1-f64d-4b57-86bd-2d0fb2aa5e18 · outbound

This paper cites Okapi at trec-3,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Okapi at trec-3,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T21:38:08.020603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab055f65-5001-4eed-b335-c1a7ad5c1f37 · outbound

This paper cites Dense Passage Retrieval for Open-Domain Question Answering.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Dense Passage Retrieval for Open-Domain Question Answering

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-11T21:38:08.023422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40e90e88-5c09-4252-a783-859785ae239d · outbound

This paper cites Experimental approach toward training and analysing siamese deep neural network for sentence with no repeated expressions,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Experimental approach toward training and analysing siamese deep neural network for sentence with no repeated expressions,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:38:08.276960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e0b0b2d5-de78-463e-8123-5029dc60b3e3 · outbound

This paper cites Reciprocal rank fusion outperforms condorcet and individual rank learning methods,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Reciprocal rank fusion outperforms condorcet and individual rank learning methods,

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-11T21:38:08.029932Z

Source-reported events for the cited work

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Observation a46a74d1-52ae-4427-be74-aa57316063f1 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations LoRA: Low-Rank Adaptation of Large Language Models

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-11T21:38:08.033704Z

Source-reported events for the cited work

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Observation b11870b6-c019-4613-8a3a-26b1acc224f1 · outbound

This paper cites How to fine-tune: Focus on effective datasets,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations How to fine-tune: Focus on effective datasets,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T21:38:08.261613Z

Source-reported events for the cited work

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Observation 0238773b-dd3e-4e10-b25c-0dc4b2522bb3 · outbound

This paper cites Stanford alpaca: An instruction-following llama model,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Stanford alpaca: An instruction-following llama model,

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-11T21:38:08.039684Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1efbe060-475a-42c7-9487-e3470c735e37 · outbound

This paper cites Rouge: A package for automatic evaluation of summaries,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Rouge: A package for automatic evaluation of summaries,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-11T21:38:08.042608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94783fe2-5264-4d36-8a59-650bc0d78109 · outbound

This paper cites BERTScore: Evaluating Text Generation with BERT.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations BERTScore: Evaluating Text Generation with BERT

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-11T21:38:08.045670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9701622c-1db4-48bd-b303-159b4a920d42 · outbound

This paper cites Re-Examining System-Level Correlations of Automatic Summarization Evaluation Metrics.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Re-Examining System-Level Correlations of Automatic Summarization Evaluation Metrics

Reference 41

Resolution: verified exact; local_arxiv, observed 2026-08-11T21:38:08.099209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 006c99f0-8978-431b-a5bf-aaefcc99bbca · outbound

This paper cites Consultation Checklists: Standardising the Human Evaluation of Medical Note Generation.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Consultation Checklists: Standardising the Human Evaluation of Medical Note Generation

Reference 42

Resolution: verified exact; local_arxiv, observed 2026-08-11T21:38:08.086000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4956c692-6b78-4788-8ede-334f9b41c8c8 · outbound

This paper cites Interrater reliability: the kappa statistic,.

CLINICSUM: Utilizing Language Models for Generating Clinical Summaries from Patient-Doctor Conversations Interrater reliability: the kappa statistic,

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-11T21:38:08.055134Z

Source-reported events for the cited work

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Pith citing papers

No inbound Pith citation observations are available.