Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2307.02179.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T21:19:30.128678Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-17T08:39:28.164364Z
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 8d9c085d-6e39-4ae5-8ef4-c2bd198a7064 · inbound
"Do Anything Now": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models Open-Source LLMs for Text Annotation: A Practical Guide for Model Setting and Fine-Tuning
Reference 12
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation e3bfb64a-b552-4833-937c-372c05629403 · inbound
Reliable Annotations with Less Effort: Evaluating LLM-Human Collaboration in Search Clarifications Open-Source LLMs for Text Annotation: A Practical Guide for Model Setting and Fine-Tuning
Reference 7
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation db92829f-04e8-4e15-9388-a6100d99a3d8 · inbound
ACD-CLIP: Decoupling Representation and Dynamic Fusion for Zero-Shot Anomaly Detection Open-Source LLMs for Text Annotation: A Practical Guide for Model Setting and Fine-Tuning
Reference 2023
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1d58986c-7e14-4e38-8c82-ee71a1672364 · inbound
Evaluating Large Language Models as Expert Annotators Open-Source LLMs for Text Annotation: A Practical Guide for Model Setting and Fine-Tuning
Reference 3
Source-reported events for the cited work
Unavailable: canonical work link unavailable.