Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2311.01463.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T14:46:29.530844Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
0 of 0 outbound references displayed
External citation measurements
19
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
No outbound reference observations are available for this paper version.
Observation 929df44a-c71a-4cc0-b6d9-efd276349e7e · inbound
AI Safety Landscape for Large Language Models: Taxonomy, State-of-the-art, and Future Directions Creating Trustworthy LLMs: Dealing with Hallucinations in Healthcare AI
Reference 6
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 779c328c-30d0-43a4-8ef6-dea6821ee3e0 · inbound
Enhancing Trust in Large Language Models via Uncertainty-Calibrated Fine-Tuning Creating Trustworthy LLMs: Dealing with Hallucinations in Healthcare AI
Reference 3
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 1283dea7-4db4-486d-b74a-b7deb8fde1f0 · inbound
Automatic Evaluation of Healthcare LLMs Beyond Question-Answering Creating Trustworthy LLMs: Dealing with Hallucinations in Healthcare AI
Reference 3
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 041867c6-1d6c-4b4e-80af-ed3416e6a642 · inbound
TerraMAE: Learning Spatial-Spectral Representations from Hyperspectral Earth Observation Data via Adaptive Masked Autoencoders Creating Trustworthy LLMs: Dealing with Hallucinations in Healthcare AI
Reference 2
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 26adc0fc-6091-4403-9851-eabc5d1c763a · inbound
Trustworthy Medical Imaging with Large Language Models: A Study of Hallucinations Across Modalities Creating Trustworthy LLMs: Dealing with Hallucinations in Healthcare AI
Reference 2
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5ef117af-c04a-4e65-b0ed-7bd061f577b0 · inbound
Trustworthy Agents for Electronic Health Records through Confidence Estimation Creating Trustworthy LLMs: Dealing with Hallucinations in Healthcare AI
Reference 2
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3554c3fb-4bc1-4c77-a82d-f092b7acde90 · inbound
An Agentic Model Context Protocol Framework for Medical Concept Standardization Creating Trustworthy LLMs: Dealing with Hallucinations in Healthcare AI
Reference 2023
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 81e8387f-d976-45d3-8a7e-9b59c83d83c9 · inbound
A global log for medical AI Creating Trustworthy LLMs: Dealing with Hallucinations in Healthcare AI
Reference 18
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b6183e3a-4e35-451d-a55c-690402e9bd76 · inbound
Not All Needles Are Found: How Fact Distribution and Don't Make It Up Prompts Shape Retrieval, Reasoning, and Hallucination in Long-Context LLMs Creating Trustworthy LLMs: Dealing with Hallucinations in Healthcare AI
Reference 40
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d1fd8e9d-48ca-4c1a-8e3b-e9d90a5da15e · inbound
Do No Harm? Hallucination and Actor-Level Abuse in Web-Deployed Medical Large Language Models Creating Trustworthy LLMs: Dealing with Hallucinations in Healthcare AI
Reference 67
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 8cec5fb9-8fee-4d1c-a16e-92c5abc75acc · inbound
Explicit Evidence Grounding via Structured Inline Citation Generation Creating Trustworthy LLMs: Dealing with Hallucinations in Healthcare AI
Reference 29
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 174d07d2-db9f-47e7-b8c1-f96f1a1e24b7 · inbound
How Do LLMs Cite? A Mechanistic Interpretation of Attribution in Retrieval-Augmented Generation Creating Trustworthy LLMs: Dealing with Hallucinations in Healthcare AI
Reference 1
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.