Paper Citation Record · LEDGER

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs

As of 17 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2504.16394.

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

pith.paper-citation-record.v1
2504.16394 v3

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:09:14.013775Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

34 of 34 outbound references displayed

verified exact6
verified fuzzy2
unresolved25
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fb6a5e02-21de-4581-b7d3-d70ae309a45a · outbound

This paper cites HealthGAT: Node Classifications in Electronic Health Records using Graph Attention Networks.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs HealthGAT: Node Classifications in Electronic Health Records using Graph Attention Networks

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-08-16T11:09:14.382133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9dcd59d4-a32e-4a9f-bd51-d6cb7c85a14d · outbound

This paper cites Gemma 3 Technical Report.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs Gemma 3 Technical Report

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:13.921257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a104220-9fd1-4feb-9ba9-593e030abdb1 · outbound

This paper cites MediSwift: Efficient Sparse Pre-trained Biomedical Language Models.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs MediSwift: Efficient Sparse Pre-trained Biomedical Language Models

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-16T11:09:14.331954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 86f0ddf2-678e-4897-8385-2cc9929c5517 · outbound

This paper cites BioMedLM: A 2.7B Parameter Language Model Trained On Biomedical Text.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs BioMedLM: A 2.7B Parameter Language Model Trained On Biomedical Text

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:13.931700Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40fec7b8-3e87-492b-a091-d735417237ea · outbound

This paper cites LongRecipe: Recipe for Efficient Long Context Generalization in Large Language Models.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs LongRecipe: Recipe for Efficient Long Context Generalization in Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:13.934717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab625597-730a-474d-8f76-38506d187e28 · outbound

This paper cites A comprehensive study on quantization techniques for large language models.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs A comprehensive study on quantization techniques for large language models

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:09:14.413038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9d92a9f2-ac20-4417-8de3-a324d9d79891 · outbound

This paper cites Enabling Scalable Evaluation of Bias Patterns in Medical LLMs.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs Enabling Scalable Evaluation of Bias Patterns in Medical LLMs

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-16T11:09:14.301269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d20252f0-0f2f-434e-a725-75e472a85be4 · outbound

This paper cites Aligning (Medical) LLMs for (Counterfactual) Fairness.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs Aligning (Medical) LLMs for (Counterfactual) Fairness

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:13.943472Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f9b5dc7-dced-423b-8d60-278571a9f899 · outbound

This paper cites Large Language Models Can Learn Temporal Reasoning.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs Large Language Models Can Learn Temporal Reasoning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:13.946357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db5a04f4-b806-4901-86df-7aa30d31f777 · outbound

This paper cites On Context Utilization in Summarization with Large Language Models.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs On Context Utilization in Summarization with Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:13.949019Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d48ead45-4261-4d01-9575-2c5058218b54 · outbound

This paper cites Ada-LEval: Evaluating long-context LLMs with length-adaptable benchmarks.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs Ada-LEval: Evaluating long-context LLMs with length-adaptable benchmarks

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:13.952024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc62f142-783a-4e73-a072-54934be6b347 · outbound

This paper cites Evaluating and mitigating limitations of large language models in clinical decision making.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs Evaluating and mitigating limitations of large language models in clinical decision making

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:09:14.402626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 94ddb57f-f544-4155-bd41-ee60b760182d · outbound

This paper cites Optimal path for Biomedical Text Summarization Using Pointer GPT.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs Optimal path for Biomedical Text Summarization Using Pointer GPT

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-08-16T11:09:14.183525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 70360f32-8b0a-43c3-8883-310421c0fd03 · outbound

This paper cites Large Language Models Are Reasoning Teachers.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs Large Language Models Are Reasoning Teachers

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:13.967499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc7340ec-f6de-469d-be06-bc609b3f6491 · outbound

This paper cites Teaching Small Language Models to Reason.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs Teaching Small Language Models to Reason

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:13.970853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6b2d7a8-3217-43ec-800f-a90f9cf3847a · outbound

This paper cites Rho-1: Not All Tokens Are What You Need.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs Rho-1: Not All Tokens Are What You Need

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:13.973481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4c6d4ca-f62d-4d19-b7b9-2d48a664c51c · outbound

This paper cites Sparser is Faster and Less is More: Efficient Sparse Attention for Long-Range Transformers.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs Sparser is Faster and Less is More: Efficient Sparse Attention for Long-Range Transformers

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:13.976173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ddd772ad-efa4-4fda-94f4-554379d45f11 · outbound

This paper cites Knowledge Graphs: Opportunities and Challenges.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs Knowledge Graphs: Opportunities and Challenges

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:13.979217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf78c193-aa28-4090-863f-33e226a0b526 · outbound

This paper cites Biomedical Knowledge Graph: A Survey of Domains, Tasks, and Real-World Applications.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs Biomedical Knowledge Graph: A Survey of Domains, Tasks, and Real-World Applications

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:13.985075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb0a7b46-b648-476e-9138-b264730e74ea · outbound

This paper cites doi: 10.18653/v1/2024.bionlp-1.23.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs doi: 10.18653/v1/2024.bionlp-1.23

Reference 26

Resolution: verified exact; doi, observed 2026-08-16T11:09:14.047497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1d3ac6d1-7dbd-4cb5-88aa-760d63f05470 · outbound

This paper cites A dataset and benchmark for hospital course summarization with adapted large language models.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs A dataset and benchmark for hospital course summarization with adapted large language models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:13.991102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9db50f28-084e-42ec-878c-5f97d8ad790f · outbound

This paper cites Longformer: The Long-Document Transformer.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs Longformer: The Long-Document Transformer

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:13.993669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c027b298-ca86-4493-a206-82114fe9c1f1 · outbound

This paper cites Scaling Instruction-Finetuned Language Models.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs Scaling Instruction-Finetuned Language Models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:13.999256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89413c88-34dc-40f5-aa6d-63d2ccbbcb31 · outbound

This paper cites BioGPT: generative pre-trained transformer for biomedical text generation and mining.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs BioGPT: generative pre-trained transformer for biomedical text generation and mining

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:14.002051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 432efc63-24ed-41a7-b736-f068b8dd6a73 · outbound

This paper cites From Local to Global: A Graph RAG Approach to Query-Focused Summarization.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs From Local to Global: A Graph RAG Approach to Query-Focused Summarization

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:14.010856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5ceedd1-1635-4c8a-bd1f-561285178e4a · outbound

This paper cites an unresolved cited work.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs Unresolved cited work

Reference 35

Resolution: malformed identifier; raw_fallback, observed 2026-08-16T11:09:14.392282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 65bd2216-2782-4217-b8e9-070ef8beb42c · outbound

This paper cites BERTScore: Evaluating Text Generation with BERT.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs BERTScore: Evaluating Text Generation with BERT

Reference 2004

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:14.005015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c8e40a3-ddeb-4128-b4c0-f783212dac9f · outbound

This paper cites Do Transformer Modifications Transfer Across Implementations and Applications?.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs Do Transformer Modifications Transfer Across Implementations and Applications?

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:14.007990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87801c72-666a-455c-8aba-6aacae4a13a2 · outbound

This paper cites BioBART: Pretraining and Evaluation of A Biomedical Generative Language Model.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs BioBART: Pretraining and Evaluation of A Biomedical Generative Language Model

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:13.996658Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 583dd252-e075-4be4-af50-e0dc95bab40a · outbound

This paper cites Automatic summarization of doctor-patient encounter dialogues using large language model through prompt tuning.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs Automatic summarization of doctor-patient encounter dialogues using large language model through prompt tuning

Reference 2021

Resolution: verified exact; raw_fallback, observed 2026-08-16T11:09:14.250614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d34046e4-fe33-4b84-a1d2-5a21a946701f · outbound

This paper cites Distilling the Knowledge in a Neural Network.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs Distilling the Knowledge in a Neural Network

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:13.964518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76bd6b1f-c0a0-4ad9-863e-e3623e168bad · outbound

This paper cites The Llama 3 Herd of Models.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs The Llama 3 Herd of Models

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:13.918373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb44246c-d650-46f5-85c6-13d14858adcc · outbound

This paper cites GPT-4 Technical Report.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs GPT-4 Technical Report

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:13.914970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf4bf3b1-a9a1-4909-8154-01c359a42940 · outbound

This paper cites BioInstruct: Instruction Tuning of Large Language Models for Biomedical Natural Language Processing.

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs BioInstruct: Instruction Tuning of Large Language Models for Biomedical Natural Language Processing

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:13.924785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.