Paper Citation Record · LEDGER

Revisiting Large Language Models as Zero-shot Relation Extractors

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2310.05028.

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

pith.paper-citation-record.v1
2310.05028 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:56:31.606057Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T09:56:04.423133Z

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 49cacce0-9628-4f31-b0a8-a4d26242b1ad · inbound

GLiREL -- Generalist Model for Zero-Shot Relation Extraction cites this paper.

GLiREL -- Generalist Model for Zero-Shot Relation Extraction Revisiting Large Language Models as Zero-shot Relation Extractors

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T21:56:31.606057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation de0020d1-3bd6-4cf7-8a3d-535e121a91a9 · inbound

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO cites this paper.

Beyond path selection: Better LLMs for Scientific Information Extraction with MimicSFT and Relevance and Rule-induced(R$^2$)GRPO Revisiting Large Language Models as Zero-shot Relation Extractors

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T13:21:19.586236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4eb078c7-4f3e-47ca-b29b-83ed5a14c89f · inbound

What's on My Network? Using Large Language Models to Identify Real-World IoT Devices at Scale cites this paper.

What's on My Network? Using Large Language Models to Identify Real-World IoT Devices at Scale Revisiting Large Language Models as Zero-shot Relation Extractors

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-04T15:25:34.781659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbe5161c-3353-4ae4-873a-1f96109d416d · inbound

MicLog: Towards Accurate and Efficient LLM-based Log Parsing via Progressive Meta In-Context Learning cites this paper.

MicLog: Towards Accurate and Efficient LLM-based Log Parsing via Progressive Meta In-Context Learning Revisiting Large Language Models as Zero-shot Relation Extractors

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T11:17:08.456987Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d12be776-96ef-4b09-a240-bb5c9ff97fea · inbound

Relational Probing: LM-to-Graph Adaptation for Financial Prediction cites this paper.

Relational Probing: LM-to-Graph Adaptation for Financial Prediction Revisiting Large Language Models as Zero-shot Relation Extractors

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:56:04.427025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2507355b-f7a0-4fd9-b75f-69e4079c4430 · inbound

LA-RL: Label-Aware Self-Reflection for Reinforcement Learning in Information Extraction cites this paper.

LA-RL: Label-Aware Self-Reflection for Reinforcement Learning in Information Extraction Revisiting Large Language Models as Zero-shot Relation Extractors

Reference 176

Resolution: unresolved; no resolver link, observed 2026-07-30T22:49:43.497627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.