Paper Citation Record · LEDGER

Can large language models be privacy preserving and fair medical coders?

As of 15 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2412.05533.

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

pith.paper-citation-record.v1
2412.05533 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:41:42.404387Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+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

27 of 27 outbound references displayed

verified exact1
verified fuzzy7
unresolved19
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d0660e66-29d0-48fa-b5e5-df673b759bce · outbound

This paper cites Deep learning with differential privacy.

Can large language models be privacy preserving and fair medical coders? Deep learning with differential privacy

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T20:41:42.251709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c73d6ebe-7e85-4e1c-87ed-0221e5ff6234 · outbound

This paper cites On the accuracy and efficiency of group-wise clipping in differentially private optimization.

Can large language models be privacy preserving and fair medical coders? On the accuracy and efficiency of group-wise clipping in differentially private optimization

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T20:41:42.257683Z

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Unavailable: canonical work link unavailable.

Observation 69782e2a-6f2e-42b5-ba50-8061c058f85c · outbound

This paper cites Differentially private optimization on large model at small cost.

Can large language models be privacy preserving and fair medical coders? Differentially private optimization on large model at small cost

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:41:43.158694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 44b441a5-855f-46d2-8e9b-224805eb551f · outbound

This paper cites Extracting training data from large language models.

Can large language models be privacy preserving and fair medical coders? Extracting training data from large language models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T20:41:42.268257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4c97a3a-4766-4526-b45b-d243b1b8556d · outbound

This paper cites Membership inference attacks from first principles.

Can large language models be privacy preserving and fair medical coders? Membership inference attacks from first principles

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:41:43.125398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 521a9073-140f-46e4-ad8a-ede222aee540 · outbound

This paper cites MEDITRON-70B: Scaling Medical Pretraining for Large Language Models.

Can large language models be privacy preserving and fair medical coders? MEDITRON-70B: Scaling Medical Pretraining for Large Language Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T20:41:42.280092Z

Source-reported events for the cited work

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Observation 9fc383bd-6689-4568-a4b2-caee13937f32 · outbound

This paper cites The algorithmic foundations of differential privacy.

Can large language models be privacy preserving and fair medical coders? The algorithmic foundations of differential privacy

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T20:41:42.286012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f195632d-4c62-4c50-85ec-804aaa5dbca4 · outbound

This paper cites Havtorn, Lasse Borgholt, Maria Maistro, Tuukka Ruotsalo, and Lars Maaløe.

Can large language models be privacy preserving and fair medical coders? Havtorn, Lasse Borgholt, Maria Maistro, Tuukka Ruotsalo, and Lars Maaløe

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T20:41:42.297141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee96eb53-f002-479c-96d6-fff3e3833733 · outbound

This paper cites Numerical composition of differential privacy.

Can large language models be privacy preserving and fair medical coders? Numerical composition of differential privacy

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T20:41:42.302723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17428716-5a4a-4ea3-9844-38f3a0c5b1e3 · outbound

This paper cites PLM - ICD : Automatic ICD coding with pretrained language models.

Can large language models be privacy preserving and fair medical coders? PLM - ICD : Automatic ICD coding with pretrained language models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T20:41:42.308209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73203d1e-3c51-4a8c-af46-4935d06fcafe · outbound

This paper cites Mimic-iii, a freely accessible critical care database.

Can large language models be privacy preserving and fair medical coders? Mimic-iii, a freely accessible critical care database

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T20:41:42.314483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48f3ce42-346e-476b-aff2-fe561f8669a7 · outbound

This paper cites Computing tight differential privacy guarantees using fft.

Can large language models be privacy preserving and fair medical coders? Computing tight differential privacy guarantees using fft

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T20:41:42.321089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a97b95f-ef2a-49d8-bd36-c02bd10fa015 · outbound

This paper cites ICD Coding from Clinical Text Using Multi-Filter Residual Convolutional Neural Network.

Can large language models be privacy preserving and fair medical coders? ICD Coding from Clinical Text Using Multi-Filter Residual Convolutional Neural Network

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-11T20:41:42.844809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 50dd206a-d8b9-442c-be59-32b091084c68 · outbound

This paper cites Large language models can be strong differentially private learners.

Can large language models be privacy preserving and fair medical coders? Large language models can be strong differentially private learners

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:41:43.050858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation beda9542-5eb7-4b5b-b8f7-c05b30c2985b · outbound

This paper cites Learning Differentially Private Recurrent Language Models.

Can large language models be privacy preserving and fair medical coders? Learning Differentially Private Recurrent Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T20:41:42.337136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4df76e27-8025-4289-9f4b-b229ff70098e · outbound

This paper cites Quantifying privacy risks of masked language models using membership inference attacks.

Can large language models be privacy preserving and fair medical coders? Quantifying privacy risks of masked language models using membership inference attacks

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T20:41:42.342852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2691107-d5c5-4130-84cf-8eec231f2378 · outbound

This paper cites R\'enyi Differential Privacy of the Sampled Gaussian Mechanism.

Can large language models be privacy preserving and fair medical coders? R\'enyi Differential Privacy of the Sampled Gaussian Mechanism

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T20:41:42.348084Z

Source-reported events for the cited work

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Observation 4be9a49b-25b0-40d1-93a2-62b195233612 · outbound

This paper cites Explainable prediction of medical codes from clinical text.

Can large language models be privacy preserving and fair medical coders? Explainable prediction of medical codes from clinical text

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T20:41:42.353453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35bebb67-d8a3-4d04-a74f-850308ef70a0 · outbound

This paper cites Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters.

Can large language models be privacy preserving and fair medical coders? Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:41:43.035634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2c59c74c-93e9-40ad-bbac-2350fe58f18d · outbound

This paper cites Suriyakumar, Nicolas Papernot, Anna Goldenberg, and Marzyeh Ghassemi.

Can large language models be privacy preserving and fair medical coders? Suriyakumar, Nicolas Papernot, Anna Goldenberg, and Marzyeh Ghassemi

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T20:41:42.363558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12f4c479-58df-4a1e-92c8-35c8f8bf3fdb · outbound

This paper cites A Label Attention Model for ICD Coding from Clinical Text.

Can large language models be privacy preserving and fair medical coders? A Label Attention Model for ICD Coding from Clinical Text

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T20:41:42.369928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a3ea175e-5718-41e4-957a-9390b81699d5 · outbound

This paper cites Multi-stage retrieve and re-rank model for automatic medical coding recommendation.

Can large language models be privacy preserving and fair medical coders? Multi-stage retrieve and re-rank model for automatic medical coding recommendation

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:41:43.017546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7f96a810-56a7-404b-a878-55bf1072aee7 · outbound

This paper cites Subsampled r \'e nyi differential privacy and analytical moments accountant.

Can large language models be privacy preserving and fair medical coders? Subsampled r \'e nyi differential privacy and analytical moments accountant

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:41:42.996485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c99b2d7b-84bd-489b-8b3a-8931c24aa3c1 · outbound

This paper cites HuggingFace's Transformers: State-of-the-art Natural Language Processing.

Can large language models be privacy preserving and fair medical coders? HuggingFace's Transformers: State-of-the-art Natural Language Processing

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T20:41:42.386378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05fcce30-2660-4920-863b-ea103ce9a283 · outbound

This paper cites Yu, and Yangyong Zhu.

Can large language models be privacy preserving and fair medical coders? Yu, and Yangyong Zhu

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T20:41:42.391517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7680a347-75dd-42a3-89a3-af163aa199ea · outbound

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

Can large language models be privacy preserving and fair medical coders? A large language model for electronic health records

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:41:42.977149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f9154b35-accc-429c-825c-3f958e1d906f · outbound

This paper cites Knowledge injected prompt based fine-tuning for multi-label few-shot ICD coding.

Can large language models be privacy preserving and fair medical coders? Knowledge injected prompt based fine-tuning for multi-label few-shot ICD coding

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T20:41:42.404387Z

Source-reported events for the cited work

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Pith citing papers

No inbound Pith citation observations are available.