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Paper Citation Record · LEDGER

Retrieval-Augmented Code Generation for Universal Information Extraction

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2311.02962.

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

pith.paper-citation-record.v1
2311.02962 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:52:18.902876Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 24f7bc6f-0c8e-4832-b98a-4f7bbe8e262b · inbound

Retrieval-Augmented Generation for AI-Generated Content: A Survey cites this paper.

Retrieval-Augmented Generation for AI-Generated Content: A Survey Retrieval-Augmented Code Generation for Universal Information Extraction

Reference 258

Resolution
verified exact
arxiv_id, observed 2026-05-15T13:32:17.554723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-15T13:32:17.177021Z digest=sha256:c4145f658acbb51e9bb951594a99a9ceb3a4283e53f7625c87468b2e27041483

Observation f0ab4640-f7c4-450b-8abd-64a9a3afe849 · 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 Retrieval-Augmented Code Generation for Universal Information Extraction

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-11T15:05:32.462222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T15:05:32.462222Z digest=sha256:edb6aa33aca7a8550f4e7424a635b2271a75a48b2803cc38bf0e40262833905f

Observation 2266646e-f5d2-4bd2-a3f1-613a6de1cf46 · inbound

Adaptive Schema-aware Event Extraction with Retrieval-Augmented Generation cites this paper.

Adaptive Schema-aware Event Extraction with Retrieval-Augmented Generation Retrieval-Augmented Code Generation for Universal Information Extraction

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-15T21:52:18.902876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:52:18.902876Z digest=sha256:59689c23359b6a55558f74a0dc32ee93272ef0cc4bc21068c6b6838e750c58be

Observation e5babf06-090f-40c3-96c3-8a697415b7b6 · 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 Retrieval-Augmented Code Generation for Universal Information Extraction

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T15:10:10.272006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:10:10.272006Z digest=sha256:c2dea10c69659f6a65d84f01bd7ff916ed87797f7fe77221f2dda7dca4951562

Observation b5c16ce1-9fea-4625-8450-e8313d88134b · inbound

Schema as Parameterized Tools for Universal Information Extraction cites this paper.

Schema as Parameterized Tools for Universal Information Extraction Retrieval-Augmented Code Generation for Universal Information Extraction

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T11:50:45.602034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:50:45.602034Z digest=sha256:8601e983b5320efc179e63d379f52636458719c1127aad1d0c6c62c16c701112

Observation c532402f-7083-4cc6-bc65-4c0079cc31dc · inbound

KnowCoder-V2: Deep Knowledge Analysis cites this paper.

KnowCoder-V2: Deep Knowledge Analysis Retrieval-Augmented Code Generation for Universal Information Extraction

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T05:51:44.509211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:51:44.509211Z digest=sha256:7de9f8cdb2b80b0713e55123dbba8a49b0ebc2bf0f6b7f8768423c213c5044d2

Observation ba662dbb-808f-49c1-bf8e-465ca5fbec41 · inbound

SACL: Understanding and Combating Textual Bias in Code Retrieval with Semantic-Augmented Reranking and Localization cites this paper.

SACL: Understanding and Combating Textual Bias in Code Retrieval with Semantic-Augmented Reranking and Localization Retrieval-Augmented Code Generation for Universal Information Extraction

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T23:02:57.375769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:02:57.375769Z digest=sha256:e6fe9b9c25a53ed1c29cb068128ffb87036c0b2fac854c816858a18e7ce047c9

Observation 33e82b85-6b94-4224-a1da-03964cc0b3f2 · inbound

MemoCoder: Automated Function Synthesis using LLM-Supported Agents cites this paper.

MemoCoder: Automated Function Synthesis using LLM-Supported Agents Retrieval-Augmented Code Generation for Universal Information Extraction

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-15T18:13:22.777857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:13:22.777857Z digest=sha256:3d5936ffb437d2064c0f5a97a46783d30ff3d4c57c71d68cc22e1d44cc54bd53

Observation 9d2bd02b-5d17-42ff-861c-b3de244b59a3 · inbound

Joint Information Extraction Across Classical and Modern Chinese with Tea-MOELoRA cites this paper.

Joint Information Extraction Across Classical and Modern Chinese with Tea-MOELoRA Retrieval-Augmented Code Generation for Universal Information Extraction

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-05T12:54:05.422943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T12:54:05.422943Z digest=sha256:10959d27c550a18964a3b04af24e27ea58c8950cc8657bfe2348eddebecff58b

Observation 4c4cf28e-de65-49d7-b432-4f37bfe33edd · inbound

LC-ICL: Label-Guided Contrastive In-Context Learning for Robust Information Extraction cites this paper.

LC-ICL: Label-Guided Contrastive In-Context Learning for Robust Information Extraction Retrieval-Augmented Code Generation for Universal Information Extraction

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-06-30T07:34:20.787392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-30T07:33:12.712241Z digest=sha256:b6f9db9fbe2ca0e430db23c70938f723f800e183f22c62ebc425a3e0bb8d35b2

Observation 4bf0870c-ded6-41cb-a199-e5814cf194d0 · inbound

Beyond Clean Text: Evaluating Encoder and Decoder Robustness for Bangla Event Detection in Noisy Text cites this paper.

Beyond Clean Text: Evaluating Encoder and Decoder Robustness for Bangla Event Detection in Noisy Text Retrieval-Augmented Code Generation for Universal Information Extraction

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-07-01T06:05:29.546824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-07-01T01:46:18.576571Z digest=sha256:a1163ccc4ede6f6895c97121040effb791fa470ccc259a92a692e8d0aaf4d6b0

Observation 56294a99-9ea6-4d02-868a-f9ae9d2d7aa0 · 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 Retrieval-Augmented Code Generation for Universal Information Extraction

Reference 61

Resolution
unresolved
no resolver link, observed 2026-07-30T22:49:43.135996Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-30T22:49:43.135996Z digest=sha256:03f8c00d1716db28007e829d73e211a15e534260b8e4691b8eb532e1476d94b1