Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Do Prompt-Based Models Really Understand the Meaning of their Prompts?
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2109.01247.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T13:57:11.478970Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T04:06:34.906379Z
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 d2cbba3d-fe0e-45bf-9f88-23400e86a71f · inbound
Multitask Prompted Training Enables Zero-Shot Task Generalization cites this paper.
Multitask Prompted Training Enables Zero-Shot Task Generalization Do Prompt-Based Models Really Understand the Meaning of their Prompts?
Reference 66
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-14T17:59:43.239507Z
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 468806fe-57e1-4417-9b95-ec668a8d4753 · inbound
Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them cites this paper.
Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them Do Prompt-Based Models Really Understand the Meaning of their Prompts?
Reference 29
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T07:15:24.008493Z
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 7aa1c6e6-e2b1-4ba4-91e8-adfd19d5ce09 · inbound
Large Language Models Are Human-Level Prompt Engineers cites this paper.
Large Language Models Are Human-Level Prompt Engineers Do Prompt-Based Models Really Understand the Meaning of their Prompts?
Reference 34
- Resolution
- verified exact
- arxiv_id, observed 2026-05-24T09:43:26.356199Z
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 8600aa5f-320b-4fa3-ba64-f06bd0e88f33 · inbound
Multi-Agent Language Models: Advancing Cooperation, Coordination, and Adaptation cites this paper.
Multi-Agent Language Models: Advancing Cooperation, Coordination, and Adaptation Do Prompt-Based Models Really Understand the Meaning of their Prompts?
Reference 46
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T04:57:25.739518Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1a7c2b15-4db1-4b08-9be8-3474bebd8358 · inbound
Understanding Human Limits in Pattern Recognition: A Computational Model of Sequential Reasoning in Rock, Paper, Scissors cites this paper.
Understanding Human Limits in Pattern Recognition: A Computational Model of Sequential Reasoning in Rock, Paper, Scissors Do Prompt-Based Models Really Understand the Meaning of their Prompts?
Reference 60
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:26:03.588558Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 47bd2fa6-47b3-415e-92c1-edc5ac339907 · inbound
Characterizing initial human-AI proof formalization workflows cites this paper.
Characterizing initial human-AI proof formalization workflows Do Prompt-Based Models Really Understand the Meaning of their Prompts?
Reference 214
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T04:06:34.908012Z
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 db19dba4-69c2-4470-8fa9-744f8721c355 · inbound
Visual Grounding in Zero-Shot Vision-Language Control cites this paper.
Visual Grounding in Zero-Shot Vision-Language Control Do Prompt-Based Models Really Understand the Meaning of their Prompts?
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:57:11.478970Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.