Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Automatic Engineering of Long Prompts
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2311.10117.
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 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T19:07:07.235544Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T17:39:41.676680Z
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 83002243-54b3-4293-bdde-a813c87e76db · inbound
Unveiling Uncertainty: A Deep Dive into Calibration and Performance of Multimodal Large Language Models cites this paper.
Unveiling Uncertainty: A Deep Dive into Calibration and Performance of Multimodal Large Language Models Automatic Engineering of Long Prompts
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T12:08:03.367670Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d379dfb4-b764-4fe2-85c5-936d5038a176 · inbound
Boosting Private Domain Understanding of Efficient MLLMs: A Tuning-free, Adaptive, Universal Prompt Optimization Framework cites this paper.
Boosting Private Domain Understanding of Efficient MLLMs: A Tuning-free, Adaptive, Universal Prompt Optimization Framework Automatic Engineering of Long Prompts
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T00:08:16.195030Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0caa2560-8023-4f23-b0dc-1eee1bc559c4 · inbound
Automatic Prompt Optimization Techniques: Exploring the Potential for Synthetic Data Generation cites this paper.
Automatic Prompt Optimization Techniques: Exploring the Potential for Synthetic Data Generation Automatic Engineering of Long Prompts
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T06:02:12.837173Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f351f4f2-3a13-40cd-bef3-cb21ee16c2b8 · inbound
Evolutionary Computation and Large Language Models: A Survey of Methods, Synergies, and Applications cites this paper.
Evolutionary Computation and Large Language Models: A Survey of Methods, Synergies, and Applications Automatic Engineering of Long Prompts
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:14:07.545956Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7d3b9c1e-9f71-47ff-9866-891dc97b0702 · inbound
The Evolution of Natural Language Processing: How Prompt Optimization and Language Models are Shaping the Future cites this paper.
The Evolution of Natural Language Processing: How Prompt Optimization and Language Models are Shaping the Future Automatic Engineering of Long Prompts
Reference 148
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T19:07:07.235544Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 91d7bca0-ef4f-4814-bdcf-d8ab70425e6c · inbound
Is It Time To Treat Prompts As Code? A Multi-Use Case Study For Prompt Optimization Using DSPy cites this paper.
Is It Time To Treat Prompts As Code? A Multi-Use Case Study For Prompt Optimization Using DSPy Automatic Engineering of Long Prompts
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T20:09:17.556647Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 53f5db60-6fa1-449b-8ceb-a3438a3ce68b · inbound
Grammar-Guided Evolutionary Search for Discrete Prompt Optimisation cites this paper.
Grammar-Guided Evolutionary Search for Discrete Prompt Optimisation Automatic Engineering of Long Prompts
Reference 15
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T17:39:41.679419Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.