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Paper Citation Record · LEDGER

CodeIE: Large Code Generation Models are Better Few-Shot Information Extractors

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2305.05711.

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

pith.paper-citation-record.v1
2305.05711 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T15:05:32.513334Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-14T23:43:18.492122Z

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 5909ce5e-177a-4f9b-a880-f36337733f7d · inbound

Can AI Extract Antecedent Factors of Human Trust in AI? An Application of Information Extraction for Scientific Literature in Behavioural and Computer Sciences cites this paper.

Can AI Extract Antecedent Factors of Human Trust in AI? An Application of Information Extraction for Scientific Literature in Behavioural and Computer Sciences CodeIE: Large Code Generation Models are Better Few-Shot Information Extractors

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-11T15:05:32.513334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T15:05:32.513334Z digest=sha256:41aacff73c2c57467f1ef5ed159dcc20ec2231e57a9fad2508878bcec2ed6e04

Observation 8b7782ab-4d16-4d24-8eb3-3fb3af4dd5cd · inbound

MPL: Multiple Programming Languages with Large Language Models for Information Extraction cites this paper.

MPL: Multiple Programming Languages with Large Language Models for Information Extraction CodeIE: Large Code Generation Models are Better Few-Shot Information Extractors

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T15:10:12.145012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:10:12.145012Z digest=sha256:aecb4d2680cd5d9af70fd20456e3857e0dadf5cdc425c61256d3419843f7b424

Observation 8765c390-d529-40a6-aed6-52dfefa09c12 · inbound

RetrieveAll: A Multilingual Named Entity Recognition Framework with Large Language Models cites this paper.

RetrieveAll: A Multilingual Named Entity Recognition Framework with Large Language Models CodeIE: Large Code Generation Models are Better Few-Shot Information Extractors

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T14:24:41.911933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:24:41.911933Z digest=sha256:a3f2717364293255b81eea22ce63516a1c013f47e0aaeb5a14274ff6ed14c8e3

Observation 8fd67628-d2c4-4f7c-ae90-c635fdfb3318 · inbound

GuideX: Guided Synthetic Data Generation for Zero-Shot Information Extraction cites this paper.

GuideX: Guided Synthetic Data Generation for Zero-Shot Information Extraction CodeIE: Large Code Generation Models are Better Few-Shot Information Extractors

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T12:05:25.457966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:05:25.457966Z digest=sha256:e4aa783532f9d8df1cf5bb377a6a1f2f01b1453179b1cce015692939a8c7b5a8

Observation 6e3ef2ed-2f52-439f-a127-3c58d4eaf6d8 · inbound

KnowCoder-V2: Deep Knowledge Analysis cites this paper.

KnowCoder-V2: Deep Knowledge Analysis CodeIE: Large Code Generation Models are Better Few-Shot Information Extractors

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T05:51:44.534144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:51:44.534144Z digest=sha256:70c38c7de8fea979c14cdb696f7b8b161916dfc1ca31884ab09e012e9ee1c07f

Observation f0696460-675c-4feb-9cc7-0b74ba20f322 · inbound

A Semantic Parsing Framework for End-to-End Time Normalization cites this paper.

A Semantic Parsing Framework for End-to-End Time Normalization CodeIE: Large Code Generation Models are Better Few-Shot Information Extractors

Reference 730

Resolution
unresolved
no resolver link, observed 2026-08-06T19:09:07.694214Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:09:07.694214Z digest=sha256:fd295fb145f6f1cf1c988a53ae9bc0ea419e874f1eabc90683204583260686b5

Observation a7112e21-b828-4e8c-a4ea-b4f5c10a5dce · inbound

Analysing Lightweight Large Language Models for Biomedical Named Entity Recognition on Diverse Ouput Formats cites this paper.

Analysing Lightweight Large Language Models for Biomedical Named Entity Recognition on Diverse Ouput Formats CodeIE: Large Code Generation Models are Better Few-Shot Information Extractors

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-14T23:43:18.495546Z

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.

source=pdf_text observed=2026-05-14T23:39:35.842512Z digest=sha256:64e59e5b4e0bc675e68cd27d09a16e2bab2da040c9d64873dd64d73053b35d72