Paper Citation Record · LEDGER

LLMaAA: Making Large Language Models as Active Annotators

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2310.19596.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2310.19596 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T21:58:02.659226Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-21T20:50:36.534244Z

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 40f8b30f-9688-49c2-927f-f6c13d21e4d6 · inbound

LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods cites this paper.

LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods LLMaAA: Making Large Language Models as Active Annotators

Reference 293

Resolution: verified exact; arxiv_id, observed 2026-05-11T23:08:35.931863Z

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 76b94dd9-df7b-45f0-93f8-e27988fb705f · inbound

ACD-CLIP: Decoupling Representation and Dynamic Fusion for Zero-Shot Anomaly Detection cites this paper.

ACD-CLIP: Decoupling Representation and Dynamic Fusion for Zero-Shot Anomaly Detection LLMaAA: Making Large Language Models as Active Annotators

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-05T21:53:06.330433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f22bc1e0-d7fa-4bd8-9ba3-941f36e36b57 · inbound

Evaluating Large Language Models as Expert Annotators cites this paper.

Evaluating Large Language Models as Expert Annotators LLMaAA: Making Large Language Models as Active Annotators

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-05T21:58:02.659226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2fa23572-8b6e-4eac-bccd-62e4c9a3ae38 · inbound

PuzzleClone: A DSL-Powered Framework for Synthesizing Verifiable Data cites this paper.

PuzzleClone: A DSL-Powered Framework for Synthesizing Verifiable Data LLMaAA: Making Large Language Models as Active Annotators

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-05T18:08:44.843029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c157e29-a430-4541-b635-b0c7ded25257 · inbound

Active Domain Knowledge Acquisition with 100-Dollar Budget: Enhancing LLMs via Cost-Efficient, Expert-Involved Interaction in Sensitive Domains cites this paper.

Active Domain Knowledge Acquisition with 100-Dollar Budget: Enhancing LLMs via Cost-Efficient, Expert-Involved Interaction in Sensitive Domains LLMaAA: Making Large Language Models as Active Annotators

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-05T17:02:40.551517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d558a0f0-e019-4070-aca9-ae307ce3b304 · inbound

Towards Consistent Detection of Cognitive Distortions: LLM-Based Annotation and Dataset-Agnostic Evaluation cites this paper.

Towards Consistent Detection of Cognitive Distortions: LLM-Based Annotation and Dataset-Agnostic Evaluation LLMaAA: Making Large Language Models as Active Annotators

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-21T20:50:36.536370Z

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 1205d0b6-b9fd-4ef7-a98b-1659c3422aae · inbound

A Patient Simulation Framework for Risk Assessment of Conversational Healthcare AI: Evaluation of an Antidepressant Decision Aid cites this paper.

A Patient Simulation Framework for Risk Assessment of Conversational Healthcare AI: Evaluation of an Antidepressant Decision Aid LLMaAA: Making Large Language Models as Active Annotators

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-03T00:13:38.699173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d16cec5-34fd-4d47-9055-dca8db8ebb78 · inbound

Can We Trust a Black-box LLM? LLM Untrustworthy Boundary Detection via Bias-Diffusion and Multi-Agent Reinforcement Learning cites this paper.

Can We Trust a Black-box LLM? LLM Untrustworthy Boundary Detection via Bias-Diffusion and Multi-Agent Reinforcement Learning LLMaAA: Making Large Language Models as Active Annotators

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-11T00:30:51.265739Z

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 80067014-99d2-40f3-929f-acb6d9d6e860 · inbound

Structured Exploration and Exploitation of Label Functions for Automated Data Annotation cites this paper.

Structured Exploration and Exploitation of Label Functions for Automated Data Annotation LLMaAA: Making Large Language Models as Active Annotators

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-14T23:28:17.080675Z

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 2283a2f7-b13a-43bc-8104-72d6819679fa · inbound

A Scalable Tool for Measuring Manner and Result Verbs in Developmental Language Research cites this paper.

A Scalable Tool for Measuring Manner and Result Verbs in Developmental Language Research LLMaAA: Making Large Language Models as Active Annotators

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-05-20T17:53:36.462108Z

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 e651139f-aa4f-4d27-9c5b-efa58ac8bef6 · inbound

DE-NER : Zero-shot Named Entity Recognition via Dialogue Elicitation of Large Language Models cites this paper.

DE-NER : Zero-shot Named Entity Recognition via Dialogue Elicitation of Large Language Models LLMaAA: Making Large Language Models as Active Annotators

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-05T00:45:14.982875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.