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Paper Citation Record · LEDGER

An Empirical Study on Information Extraction using Large Language Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2305.14450.

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

pith.paper-citation-record.v1
2305.14450 v2

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 2026-08-10T06:31:04.303077+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:21:24.217212Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T16:59:58.839259Z

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 6a83e843-4d9a-4b91-98ae-d35d1d8d0ea5 · inbound

STATE ToxiCN: A Benchmark for Span-level Target-Aware Toxicity Extraction in Chinese Hate Speech Detection cites this paper.

STATE ToxiCN: A Benchmark for Span-level Target-Aware Toxicity Extraction in Chinese Hate Speech Detection An Empirical Study on Information Extraction using Large Language Models

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-10T14:21:24.217212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:21:24.217212Z digest=sha256:01efd25bac1e0558a299980b4bbccc23adb29ce7d412aec4945a6b4d75cd461e

Observation 4e8d47ec-9535-425f-b58a-9757bd6b6ac2 · 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 An Empirical Study on Information Extraction using Large Language Models

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T15:10:10.398716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:10:10.398716Z digest=sha256:48285ffeb9bc640bfa995ec7b6d9ca8987278a6ba588d3d5dd2d759e1b4e0fe4

Observation 3ace9672-d524-4fed-b6e9-3a88c4fc332a · inbound

Fine-Grained Chinese Hate Speech Understanding: Span-Level Resources, Coded Term Lexicon, and Enhanced Detection Frameworks cites this paper.

Fine-Grained Chinese Hate Speech Understanding: Span-Level Resources, Coded Term Lexicon, and Enhanced Detection Frameworks An Empirical Study on Information Extraction using Large Language Models

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-06T17:16:30.733727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:16:30.733727Z digest=sha256:2a8a3825807b9aab636128d7a4694bce6af83ec3227019a4be362de044265c19

Observation ac72c3bd-76be-488e-a54b-7e85cb4c2281 · inbound

MExplore: an entity-based visual analytics approach for medical expertise acquisition cites this paper.

MExplore: an entity-based visual analytics approach for medical expertise acquisition An Empirical Study on Information Extraction using Large Language Models

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T16:51:22.087901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:51:22.087901Z digest=sha256:e36f44d8dbf2df3e0131c3004685721aa96873b4f9fc12f3088c0fd5905bdf1b

Observation 514851a7-6174-46fe-8593-23c2124d13ea · inbound

GLiNER2: An Efficient Multi-Task Information Extraction System with Schema-Driven Interface cites this paper.

GLiNER2: An Efficient Multi-Task Information Extraction System with Schema-Driven Interface An Empirical Study on Information Extraction using Large Language Models

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T14:35:54.172614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:35:54.172614Z digest=sha256:c442fac72fe5482f934c17e21694702dc064db9f0ed1a589738a947de388be92

Observation c38022f4-9ebd-4a40-a593-92930eb7b77e · inbound

From scratch to silver: Creating trustworthy training data for patent-SDG classification using Large Language Models cites this paper.

From scratch to silver: Creating trustworthy training data for patent-SDG classification using Large Language Models An Empirical Study on Information Extraction using Large Language Models

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-04T19:27:04.834755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T19:27:04.834755Z digest=sha256:9c2b656751edcfdc15e34d37f25bbf0eee84128f446296a66a310209456a4c13

Observation 6f27bfd6-677d-4a13-b9c8-2050ad249750 · inbound

Semantic Reranking at Inference Time for Hard Examples in Rhetorical Role Labeling cites this paper.

Semantic Reranking at Inference Time for Hard Examples in Rhetorical Role Labeling An Empirical Study on Information Extraction using Large Language Models

Reference 109

Resolution
verified exact
arxiv_id, observed 2026-05-20T11:28:14.296142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-20T11:27:30.720693Z digest=sha256:5e1ca34c5592f5344e3e5a63cc6170e4e967a0baf03cfe6d41102a152f88e6a6

Observation 4787323a-0957-4bce-92ad-0fffc08a8333 · inbound

DiffuSent: Towards a Unified Diffusion Framework for Aspect-Based Sentiment Analysis cites this paper.

DiffuSent: Towards a Unified Diffusion Framework for Aspect-Based Sentiment Analysis An Empirical Study on Information Extraction using Large Language Models

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-06-28T17:12:24.487385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-28T17:10:39.275495Z digest=sha256:a86f87841451b6b04818914d0ecafcb19cdc3f433491acd31dc731b0df434df0

Observation 3550e3dd-1933-4021-ab9c-2cd1eab658a4 · inbound

Task Decomposition for Efficient Annotation cites this paper.

Task Decomposition for Efficient Annotation An Empirical Study on Information Extraction using Large Language Models

Reference 169

Resolution
verified exact
arxiv_id, observed 2026-07-04T16:59:58.840760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-26T00:00:16.588823Z digest=sha256:45f62fb86d0995857f9042c1f657604b25bcbea4f39ed9c16b310a95a1f777c1

Observation 198ae72e-2c76-46ca-b176-de47f31cf756 · inbound

JD Oxygen AI Item Center (Oxygen AIIC) V1: An Industrial-Scale LLM/VLM-Centric Solution for Item Understanding, Management, and Applications cites this paper.

JD Oxygen AI Item Center (Oxygen AIIC) V1: An Industrial-Scale LLM/VLM-Centric Solution for Item Understanding, Management, and Applications An Empirical Study on Information Extraction using Large Language Models

Reference 84

Resolution
verified exact
arxiv_id, observed 2026-07-01T17:05:51.155030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-29T04:11:05.226043Z digest=sha256:5db7e97c693ac70f98fc283643f3c78f100ddf93c262b385ecef2609dd40abb0

Observation 8f0a6e79-203c-47db-b458-a60cfdf5b51e · inbound

JD Oxygen AI Item Center (Oxygen AIIC) V1: An Industrial-Scale LLM/VLM-Centric Solution for Item Understanding, Management, and Applications cites this paper.

JD Oxygen AI Item Center (Oxygen AIIC) V1: An Industrial-Scale LLM/VLM-Centric Solution for Item Understanding, Management, and Applications An Empirical Study on Information Extraction using Large Language Models

Reference 84

Resolution
verified exact
arxiv_id, observed 2026-06-30T09:44:37.198289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-30T09:43:58.385814Z digest=sha256:65514ef129a0c942491d711843754939c799cba10bc99123c318cde04f27bc24

Observation f9517dd4-f80c-4242-8e0f-b6dee550f424 · inbound

Discourse-Aware Policy Analysis with Argumentation: A Hybrid LLM-Symbolic Framework for Disaster Governance cites this paper.

Discourse-Aware Policy Analysis with Argumentation: A Hybrid LLM-Symbolic Framework for Disaster Governance An Empirical Study on Information Extraction using Large Language Models

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-02T05:47:19.872628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T05:47:19.872628Z digest=sha256:403b2124df2a0f02df8fa7e7377bf2db699102ccb345874fecd3a8fecde102c9