Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2203.11364.
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 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T14:44:33.664133Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-13T07:37:29.988682Z
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 5c23bf0c-1574-4d9e-aa02-224d69cd80a4 · inbound
OptiSeq: Ordering Examples On-The-Fly for In-Context Learning cites this paper.
OptiSeq: Ordering Examples On-The-Fly for In-Context Learning An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T14:44:33.664133Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5e1e2af0-143d-446e-9bd5-f7283c72d788 · inbound
If You Had to Pitch Your Ideal Software -- Evaluating Large Language Models to Support User Scenario Writing for User Experience Experts and Laypersons cites this paper.
If You Had to Pitch Your Ideal Software -- Evaluating Large Language Models to Support User Scenario Writing for User Experience Experts and Laypersons An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:37:57.027675Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation da9d0ae7-9f0a-4eef-ace9-0b06c60090c5 · inbound
DICE: Dynamic In-Context Example Selection in LLM Agents via Efficient Knowledge Transfer cites this paper.
DICE: Dynamic In-Context Example Selection in LLM Agents via Efficient Knowledge Transfer An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T10:43:49.944122Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 63ee6691-8ba5-4ddf-b133-53fe0139f628 · inbound
Object Search in Partially-Known Environments via LLM-informed Model-based Planning and Prompt Selection cites this paper.
Object Search in Partially-Known Environments via LLM-informed Model-based Planning and Prompt Selection An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-07-13T19:22:24.103426Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c027ac73-8602-49dd-8ff5-a588af6921a9 · inbound
Towards Order Fairness: Mitigating LLMs Order Sensitivity through Dual Group Advantage Optimization cites this paper.
Towards Order Fairness: Mitigating LLMs Order Sensitivity through Dual Group Advantage Optimization An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T07:37:29.991486Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.