Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-09T21:07:05.535810Z
Paper Citation Record · LEDGER
Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching
As of 23 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2604.22061.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
20 of 20 outbound references displayed
- verified exact1
- verified fuzzy11
- unresolved7
- parse uncertain1
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 39b4975b-50ce-41ff-8876-3f6445bbd21a · outbound
This paper cites an unresolved cited work.
Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching Unresolved cited work
Reference 1
- Resolution
- unresolved
- raw_fallback, observed 2026-05-23T16:23:12.796133Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 1e06dabe-557e-45e2-87b6-500a5e77cf70 · outbound
This paper cites Settings.
Reference 2
- Resolution
- parse uncertain
- raw_fallback, observed 2026-05-23T16:23:12.790984Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 56ee2799-275a-4b11-8f56-3efcbdd67305 · outbound
This paper cites MET” or “NOT MET.
Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching MET” or “NOT MET
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T16:23:12.705520Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 0b6c908f-4cc8-4007-bb36-67625f9b4cc0 · outbound
This paper cites Our primary evaluation focuses on precision, recall, and Macro-F1 scores for the binary classification task of determining whether a patient meets each of the eligibility criteria.
Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching Our primary evaluation focuses on precision, recall, and Macro-F1 scores for the binary classification task of determining whether a patient meets each of the eligibility criteria
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T16:23:12.716745Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 97c35cef-d898-483d-9534-011d927e1d00 · outbound
This paper cites As shown in Figure 1, substantial performance differences arise solely from variations in how the shared representation is processed and classified.
Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching As shown in Figure 1, substantial performance differences arise solely from variations in how the shared representation is processed and classified
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T16:23:12.767748Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 531ff527-cd94-4fda-8ceb-428f9d56bc0a · outbound
This paper cites Figure 2 summarizes performance across structured-only, unstructured-only, and mixed EHR settings using Macro-F1, AUROC, and AUPRC.
Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching Figure 2 summarizes performance across structured-only, unstructured-only, and mixed EHR settings using Macro-F1, AUROC, and AUPRC
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T16:23:12.773458Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation f524f3d5-ebcd-4097-8889-be8712f35d68 · outbound
This paper cites an unresolved cited work.
Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching Unresolved cited work
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T14:46:23.065682Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation a81c469f-0ad5-4803-b2b5-f23e479f551f · outbound
This paper cites an unresolved cited work.
Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching Unresolved cited work
Reference 8
- Resolution
- unresolved
- raw_fallback, observed 2026-05-23T16:23:12.757883Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation dc3fa66b-4b26-4ad1-a488-9b55930ec228 · outbound
This paper cites As shown in Figure 5, clear performance differences are observed across model variants and evaluation settings.
Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching As shown in Figure 5, clear performance differences are observed across model variants and evaluation settings
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T16:23:12.779991Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 4ee108fa-8dec-4633-bec4-c7ff5d4fcc4c · outbound
This paper cites an unresolved cited work.
Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching Unresolved cited work
Reference 10
- Resolution
- unresolved
- raw_fallback, observed 2026-05-23T16:23:12.726107Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 29f13e7e-b302-400e-9e3c-4d1af1a74d02 · outbound
This paper cites an unresolved cited work.
Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching Unresolved cited work
Reference 11
- Resolution
- unresolved
- raw_fallback, observed 2026-05-23T16:23:12.711208Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation c6790446-86c1-44fb-baa8-cd710e1e8a39 · outbound
This paper cites potential/eligible.
Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching potential/eligible
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T16:23:12.735829Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation d2daf48a-071e-4329-8e13-2687d14fa74b · outbound
This paper cites an unresolved cited work.
Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching Unresolved cited work
Reference 13
- Resolution
- unresolved
- raw_fallback, observed 2026-05-23T16:23:12.761704Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 9f662348-8ad7-4905-9833-74b6c77cd73d · outbound
This paper cites an unresolved cited work.
Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching Unresolved cited work
Reference 14
- Resolution
- unresolved
- raw_fallback, observed 2026-05-23T16:23:12.745441Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 1d4d91ac-023f-4db9-b48c-64cd6e499720 · outbound
This paper cites RAG-encoded inputs were fed into each frozen LLM, and the resulting embeddings were passed to the same MLP classifier.
Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching RAG-encoded inputs were fed into each frozen LLM, and the resulting embeddings were passed to the same MLP classifier
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T16:23:12.752814Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 7ad2adbd-2b35-49fa-a02d-d4b0d8d62800 · outbound
This paper cites an unresolved cited work.
Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching Unresolved cited work
Reference 16
- Resolution
- unresolved
- raw_fallback, observed 2026-05-23T16:23:12.729804Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 34f15fd2-4fa1-4ec9-b84c-7d7452b8caac · outbound
This paper cites Frozen (Task 4) To evaluate the benefit of representation adaptation, we compared frozen and fine-tuned LLM representations within identical RAG-based pipelines.
Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching Frozen (Task 4) To evaluate the benefit of representation adaptation, we compared frozen and fine-tuned LLM representations within identical RAG-based pipelines
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T16:23:12.785207Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 21edbf21-dc3f-4bae-9e34-ec8425163cd1 · outbound
This paper cites Performance was compared against zero-shot methods and TrialGPT using the evaluation metrics reported in the original studies.
Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching Performance was compared against zero-shot methods and TrialGPT using the evaluation metrics reported in the original studies
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T16:23:12.721300Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 73be378f-e772-4949-b750-e33d12563e9c · outbound
This paper cites All experiments were performed using the mixed-data setting.
Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching All experiments were performed using the mixed-data setting
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T16:23:12.741048Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 0df12fac-fb4e-47e4-9ae8-8d024c8ff39f · outbound
This paper cites EliIE: An open-source information extraction system for clinical trial eligibility criteria.
Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching EliIE: An open-source information extraction system for clinical trial eligibility criteria
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-23T16:23:12.801587Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Pith citing papers
No inbound Pith citation observations are available.