Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
One Prompt is not Enough: Automated Construction of a Mixture-of-Expert Prompts
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2407.00256.
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 2026-08-11T05:33:29.829084Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T11:39:47.093974Z
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 d9a24e63-6c0f-460e-819d-978f7089815d · inbound
BrainMAP: Learning Multiple Activation Pathways in Brain Networks cites this paper.
BrainMAP: Learning Multiple Activation Pathways in Brain Networks One Prompt is not Enough: Automated Construction of a Mixture-of-Expert Prompts
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T05:33:29.829084Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c959e1d7-5a7d-41b8-87d4-af5c74723bc5 · inbound
TAME: Test-Time Adversarial Prompt Tuning via Mixture-of-Experts for Vision-Language Models cites this paper.
TAME: Test-Time Adversarial Prompt Tuning via Mixture-of-Experts for Vision-Language Models One Prompt is not Enough: Automated Construction of a Mixture-of-Expert Prompts
Reference 52
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T14:23:21.502498Z
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.
Observation 52a4c69f-903f-46f5-ac68-93efdf39484e · inbound
Towards Spec Learning: Inference-Time Alignment from Preference Pairs cites this paper.
Towards Spec Learning: Inference-Time Alignment from Preference Pairs One Prompt is not Enough: Automated Construction of a Mixture-of-Expert Prompts
Reference 104
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T11:39:47.096263Z
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.
Observation 0ace0ac1-54b9-4ba8-98e6-b38d501d9fc4 · inbound
Towards Spec Learning: Inference-Time Alignment from Preference Pairs cites this paper.
Towards Spec Learning: Inference-Time Alignment from Preference Pairs One Prompt is not Enough: Automated Construction of a Mixture-of-Expert Prompts
Reference 104
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T12:04:39.389438Z
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.
Observation a84c92ac-245e-47b8-b837-3d6346d65aad · inbound
BT-APE: A Computationally Light Backtracking Approach to Automatic Prompt Engineering for Requirements Classification cites this paper.
BT-APE: A Computationally Light Backtracking Approach to Automatic Prompt Engineering for Requirements Classification One Prompt is not Enough: Automated Construction of a Mixture-of-Expert Prompts
Reference 51
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T09:16:48.651398Z
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.