Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Enhancing Diagnostic Accuracy through Multi-Agent Conversations: Using Large Language Models to Mitigate Cognitive Bias
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2401.14589.
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 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T20:47:34.804740Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T18:51:10.203992Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation efeb6891-9587-4dca-ae04-341acabf1923 · inbound
Enhancing LLMs for Impression Generation in Radiology Reports through a Multi-Agent System cites this paper.
Enhancing LLMs for Impression Generation in Radiology Reports through a Multi-Agent System Enhancing Diagnostic Accuracy through Multi-Agent Conversations: Using Large Language Models to Mitigate Cognitive Bias
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T20:47:34.804740Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a371982d-e213-4f93-aefb-d702e58b01f6 · inbound
Planted in Pretraining, Swayed by Finetuning: A Case Study on the Origins of Cognitive Biases in LLMs cites this paper.
Planted in Pretraining, Swayed by Finetuning: A Case Study on the Origins of Cognitive Biases in LLMs Enhancing Diagnostic Accuracy through Multi-Agent Conversations: Using Large Language Models to Mitigate Cognitive Bias
Reference 2011
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T18:51:10.261801Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 97e973b7-28c1-4d0e-bc32-6cbf2fe75c15 · inbound
The Cost of Knowing: A Resource-Aware Protocol for Benchmarking Hallucination Beyond Static Leaderboards cites this paper.
The Cost of Knowing: A Resource-Aware Protocol for Benchmarking Hallucination Beyond Static Leaderboards Enhancing Diagnostic Accuracy through Multi-Agent Conversations: Using Large Language Models to Mitigate Cognitive Bias
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-07-31T23:11:43.016964Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4678126e-cc66-41ac-88c7-c515dc4b4d94 · inbound
Multi-Agent Debate Strategies: Survey, Taxonomy, and Challenges cites this paper.
Multi-Agent Debate Strategies: Survey, Taxonomy, and Challenges Enhancing Diagnostic Accuracy through Multi-Agent Conversations: Using Large Language Models to Mitigate Cognitive Bias
Reference 52
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:32:26.498975Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.