Paper Citation Record · LEDGER

Large Language Models are Few-Shot Health Learners

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 24 inbound Pith citation observations for arXiv:2305.15525.

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

pith.paper-citation-record.v1
2305.15525 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 24 of 24 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:56:12.206858Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

36
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation dd8759c9-b503-4750-94db-226798b5892e · inbound

Time-LLM: Time Series Forecasting by Reprogramming Large Language Models cites this paper.

Time-LLM: Time Series Forecasting by Reprogramming Large Language Models Large Language Models are Few-Shot Health Learners

Reference 95

Resolution: verified exact; arxiv_id, observed 2026-05-16T16:03:17.115560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0052caec-5fbb-485e-8bb9-df44946c4af0 · inbound

Large language models for artificial general intelligence (AGI): A survey of foundational principles and approaches cites this paper.

Large language models for artificial general intelligence (AGI): A survey of foundational principles and approaches Large Language Models are Few-Shot Health Learners

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:12.206858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ed5e4c1-e617-4b58-81db-6efaee64137d · inbound

SensorChat: Answering Qualitative and Quantitative Questions during Long-Term Multimodal Sensor Interactions cites this paper.

SensorChat: Answering Qualitative and Quantitative Questions during Long-Term Multimodal Sensor Interactions Large Language Models are Few-Shot Health Learners

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-09T10:50:59.388287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71cc973c-d60e-4dba-a722-dc85267570ae · inbound

RECOVER: Designing a Large Language Model-based Remote Patient Monitoring System for Postoperative Gastrointestinal Cancer Care cites this paper.

RECOVER: Designing a Large Language Model-based Remote Patient Monitoring System for Postoperative Gastrointestinal Cancer Care Large Language Models are Few-Shot Health Learners

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:45:21.233170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 987a505a-a59e-4313-a995-cd5d7e0eefbe · inbound

Time2Lang: Bridging Time-Series Foundation Models and Large Language Models for Health Sensing Beyond Prompting cites this paper.

Time2Lang: Bridging Time-Series Foundation Models and Large Language Models for Health Sensing Beyond Prompting Large Language Models are Few-Shot Health Learners

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-08T12:14:20.338389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37fc43e4-9d2b-4b8b-9a0e-d91950964857 · inbound

SocialLM: Social Signal Processing of Patient-Provider Communication using LLMs and Contextual Aggregation cites this paper.

SocialLM: Social Signal Processing of Patient-Provider Communication using LLMs and Contextual Aggregation Large Language Models are Few-Shot Health Learners

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-22T17:05:00.370516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 90f843ce-81b0-4c08-95fe-37a27526dfad · inbound

ProMind-LLM: Proactive Mental Health Care via Causal Reasoning with Sensor Data cites this paper.

ProMind-LLM: Proactive Mental Health Care via Causal Reasoning with Sensor Data Large Language Models are Few-Shot Health Learners

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:44.017870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c6a01fd-3deb-4bf0-8c01-3a7524faf027 · inbound

Few-Shot Optimization for Sensor Data Using Large Language Models: A Case Study on Fatigue Detection cites this paper.

Few-Shot Optimization for Sensor Data Using Large Language Models: A Case Study on Fatigue Detection Large Language Models are Few-Shot Health Learners

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T14:30:38.118294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4f26751-5939-4fc4-b234-a601fa2104ef · inbound

Unraveling Spatio-Temporal Foundation Models via the Pipeline Lens: A Comprehensive Review cites this paper.

Unraveling Spatio-Temporal Foundation Models via the Pipeline Lens: A Comprehensive Review Large Language Models are Few-Shot Health Learners

Reference 202

Resolution: unresolved; no resolver link, observed 2026-08-07T11:49:48.625035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e12a4c2-2cb4-40ff-8f9a-7651b4f2d1a5 · inbound

SensorLM: Learning the Language of Wearable Sensors cites this paper.

SensorLM: Learning the Language of Wearable Sensors Large Language Models are Few-Shot Health Learners

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T05:04:06.318531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bbea080f-22c6-4ef6-9785-3be6e3f3f77e · inbound

From Time Series Analysis to Question Answering: A Survey in the LLM Era cites this paper.

From Time Series Analysis to Question Answering: A Survey in the LLM Era Large Language Models are Few-Shot Health Learners

Reference 71

Resolution: verified exact; arxiv_id, observed 2026-05-19T09:32:16.018055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 51775adc-905e-4e32-a2ab-157f1eba6c25 · inbound

Mind the XAI Gap: A Human-Centered LLM Framework for Democratizing Explainable AI cites this paper.

Mind the XAI Gap: A Human-Centered LLM Framework for Democratizing Explainable AI Large Language Models are Few-Shot Health Learners

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T01:02:18.316192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e81503f4-cff5-4792-8d2c-360c4bd92ebf · inbound

Causal Graph Fuzzy LLMs: A First Introduction and Applications in Time Series Forecasting cites this paper.

Causal Graph Fuzzy LLMs: A First Introduction and Applications in Time Series Forecasting Large Language Models are Few-Shot Health Learners

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T15:04:11.287417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation afc490d6-b1c4-4640-bb75-e92a1d97fee6 · inbound

HRIPBench: Benchmarking LLMs in Harm Reduction Information Provision to Support People Who Use Drugs cites this paper.

HRIPBench: Benchmarking LLMs in Harm Reduction Information Provision to Support People Who Use Drugs Large Language Models are Few-Shot Health Learners

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T12:27:18.821978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb619425-abb4-4652-a944-7566ab621f0e · inbound

Dynamic Uncertainty-aware Multimodal Fusion for Outdoor Health Monitoring cites this paper.

Dynamic Uncertainty-aware Multimodal Fusion for Outdoor Health Monitoring Large Language Models are Few-Shot Health Learners

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-05T21:14:36.506119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c353e3be-38d1-4854-9b18-45950c70842c · inbound

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting cites this paper.

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting Large Language Models are Few-Shot Health Learners

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T11:45:28.692829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71285d82-6c24-4dc0-ba12-5a2eba00d7b1 · inbound

ConSensus: Multi-Agent Collaboration for Multimodal Sensing cites this paper.

ConSensus: Multi-Agent Collaboration for Multimodal Sensing Large Language Models are Few-Shot Health Learners

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-03T11:27:48.977482Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 825bf768-be17-40de-87d8-181f92a600df · inbound

Foundation Models Defining A New Era In Sensor-based Human Activity Recognition: A Survey And Outlook cites this paper.

Foundation Models Defining A New Era In Sensor-based Human Activity Recognition: A Survey And Outlook Large Language Models are Few-Shot Health Learners

Reference 92

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:53:08.555066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 01042d09-dda9-4759-92eb-773f0f796482 · inbound

Evaluating Visual Prompts with Eye-Tracking Data for MLLM-Based Human Activity Recognition cites this paper.

Evaluating Visual Prompts with Eye-Tracking Data for MLLM-Based Human Activity Recognition Large Language Models are Few-Shot Health Learners

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-15T19:26:31.467086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 15c51aeb-13d9-44c9-a461-f274383bbb0f · inbound

RAPTOR+: A Visually Grounded Vision-Language Framework to Improve Clinical Trust and Auditability in Automated Cancer Referral Processing cites this paper.

RAPTOR+: A Visually Grounded Vision-Language Framework to Improve Clinical Trust and Auditability in Automated Cancer Referral Processing Large Language Models are Few-Shot Health Learners

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-06-29T22:24:00.162228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 35aae286-918f-4967-b8c9-b0b1c21cc62e · inbound

TiWeaver: Unified Temporal Dynamics Modeling via Contextual Patching cites this paper.

TiWeaver: Unified Temporal Dynamics Modeling via Contextual Patching Large Language Models are Few-Shot Health Learners

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-02T01:36:25.973376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 35991ad6-4d7d-4ec9-adb2-cafe34b1ca4d · inbound

RPO-PDT: Demonstrating Role-Play-Based Knowledge Adaptation for Student Support Dialogue (Demonstration System) cites this paper.

RPO-PDT: Demonstrating Role-Play-Based Knowledge Adaptation for Student Support Dialogue (Demonstration System) Large Language Models are Few-Shot Health Learners

Reference 44

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T01:17:30.400423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 571d4ed2-2ae9-451b-a8ba-815c6fb75187 · inbound

WEQA: Wearable hEalth Question Answering with Query-Adaptive Agentic Reasoning cites this paper.

WEQA: Wearable hEalth Question Answering with Query-Adaptive Agentic Reasoning Large Language Models are Few-Shot Health Learners

Reference 39

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T21:08:58.485208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4f59491a-2977-4e9d-8ba8-cb4623852679 · inbound

Foundation Models for Epileptogenic Zone Identification in Drug-Resistant Epilepsy cites this paper.

Foundation Models for Epileptogenic Zone Identification in Drug-Resistant Epilepsy Large Language Models are Few-Shot Health Learners

Reference 33

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T09:09:42.936736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.