Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
StablePrompt: Automatic Prompt Tuning using Reinforcement Learning for Large Language Models
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2410.07652.
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 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T17:18:03.859727Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T09:16:48.655595Z
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 8e88e3bc-9da9-48d2-85bf-be95d2dfc462 · inbound
ACING: Actor-Critic for Instruction Learning in Black-Box LLMs cites this paper.
ACING: Actor-Critic for Instruction Learning in Black-Box LLMs StablePrompt: Automatic Prompt Tuning using Reinforcement Learning for Large Language Models
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T17:18:03.859727Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 425399e7-a7a5-4014-a872-bc5d5a25cb92 · inbound
Prompt Optimization for LLM Code Generation via Reinforcement Learning cites this paper.
Prompt Optimization for LLM Code Generation via Reinforcement Learning StablePrompt: Automatic Prompt Tuning using Reinforcement Learning for Large Language Models
Reference 20
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T08:53:10.318805Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 96887f62-4414-4df9-a01a-5afd00cf2b21 · 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 StablePrompt: Automatic Prompt Tuning using Reinforcement Learning for Large Language Models
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T09:16:48.656948Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.