Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2205.12548.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T04:37:28.378324Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T09:07:48.430556Z
0 of 0 outbound references displayed
External citation measurements
No source-named external measurement is stored.
No outbound reference observations are available for this paper version.
Observation 88d78e69-6e92-4862-96d1-121383366bc7 · inbound
Large Language Models as Optimizers RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning
Reference 7
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation fe76dec6-689a-4f2a-8034-f114824f7bde · inbound
Robust Adaptation of Foundation Models with Black-Box Visual Prompting RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning
Reference 34
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation bc7e9b01-f2a8-4054-9ba0-f5b095ca68cf · inbound
Commercial LLM Agents Are Already Vulnerable to Simple Yet Dangerous Attacks RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning
Reference 8
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d579cd0e-5493-453e-8983-a637d4941938 · inbound
Fast or Slow? Integrating Fast Intuition and Deliberate Thinking for Enhancing Visual Question Answering RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning
Reference 7
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1d8ed3ec-49bf-4b51-9ed1-26ae0b82aff0 · inbound
Enhancing Reasoning Capabilities of Small Language Models with Blueprints and Prompt Template Search RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning
Reference 7
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 224d88e8-ab61-4fb8-93bf-d059a9da626b · inbound
SI-Agent: An Agentic Framework for Feedback-Driven Generation and Tuning of Human-Readable System Instructions for Large Language Models RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning
Reference 18
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 75487985-9309-43ef-b8a0-89b8d87f7ec6 · inbound
DEMONSTRATE: Zero-shot Language to Robotic Control via Multi-task Demonstration Learning RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning
Reference 22
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8344a737-9e84-4b6f-b48d-f63975534ed0 · inbound
TRPrompt: Bootstrapping Query-Aware Prompt Optimization from Textual Rewards RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning
Reference 3
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3bd1bca7-01ff-4995-ab4f-ae97d6c44e1b · inbound
PIAST: Rapid Prompting with In-context Augmentation for Scarce Training data RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning
Reference 53
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 55da2032-0889-4030-b6ed-b493c56ee86f · inbound
PEEM: Prompt Engineering Evaluation Metrics for Interpretable Joint Evaluation of Prompts and Responses RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning
Reference 32
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 395c8fda-1aa3-435d-928c-c3640072b345 · inbound
Learning, Fast and Slow: Towards LLMs That Adapt Continually RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning
Reference 12
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 803935cc-b03b-412d-a9e3-80369770b8cb · inbound
Learning, Fast and Slow: Towards LLMs That Adapt Continually RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning
Reference 12
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 139d43b9-f050-42c1-b168-10468afda8a5 · inbound
Prompt Optimization for LLM Code Generation via Reinforcement Learning RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning
Reference 8
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 8f7e93f8-0978-4034-aa9a-110e29e52fd2 · inbound
Task-Aware Structured Memory for Dynamic Multi-modal In-Context Learning RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning
Reference 103
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.