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Paper Citation Record · LEDGER

LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2406.04614.

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

pith.paper-citation-record.v1
2406.04614 v1

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 2026-08-08T19:12:42.491987Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T16:48:39.805985Z

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 cf11f771-2b1a-4bde-8873-a75b651ecc03 · inbound

OntoTune: Ontology-Driven Self-training for Aligning Large Language Models cites this paper.

OntoTune: Ontology-Driven Self-training for Aligning Large Language Models LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-08T19:12:42.491987Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T19:12:42.491987Z digest=sha256:1b897aabbbe12fc9a40178d9ef4fa05e81b4a925dddf79f3cf1c2b1e2631c1eb

Observation 0d672cb7-98ac-456c-8237-060a8543e4b8 · inbound

AppealCase: A Dataset and Benchmark for Civil Case Appeal Scenarios cites this paper.

AppealCase: A Dataset and Benchmark for Civil Case Appeal Scenarios LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T15:03:48.156445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:03:48.156445Z digest=sha256:7114eeadaae63762dbbf6496079904e1240b376797dc3c7b4a2640905d32bcf1

Observation d463ea5e-138d-4a0c-b217-9622dbad6243 · inbound

ICH-Qwen: A Large Language Model Towards Chinese Intangible Cultural Heritage cites this paper.

ICH-Qwen: A Large Language Model Towards Chinese Intangible Cultural Heritage LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T13:18:13.810622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:18:13.810622Z digest=sha256:e82b68596aa542a40f1464498920d24ea674fd54a226e38cd32ff92447480cff

Observation 59e78db4-0088-4aa0-b120-7e016c521381 · inbound

ASP2LJ : An Adversarial Self-Play Laywer Augmented Legal Judgment Framework cites this paper.

ASP2LJ : An Adversarial Self-Play Laywer Augmented Legal Judgment Framework LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T04:54:28.808253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:54:28.808253Z digest=sha256:82aa0abb68999c536404555b7221343a30f46527f51420105e08c70e9607fc6d

Observation 35a82906-ce8f-421d-a617-9ea6c855bddc · inbound

When Large Language Models Meet Law: Dual-Lens Taxonomy, Technical Advances, and Ethical Governance cites this paper.

When Large Language Models Meet Law: Dual-Lens Taxonomy, Technical Advances, and Ethical Governance LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model

Reference 215

Resolution
unresolved
no resolver link, observed 2026-08-06T18:37:11.320193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:37:11.320193Z digest=sha256:01fbc08481bb365fd56d865ecd28d60ff03dcaf64afda3539efbbe71207312f9

Observation a97370f7-a6d7-4345-94cb-3f81ff85b491 · inbound

ChiMed 2.0: Advancing Chinese Medical Dataset in Facilitating Large Language Modeling cites this paper.

ChiMed 2.0: Advancing Chinese Medical Dataset in Facilitating Large Language Modeling LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T15:40:03.565487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T15:40:03.565487Z digest=sha256:306db52154a3da96b65b9ce4555e3111c0bb41eeec3d3e2bd6477613a9c2b8bc

Observation 3aa27c55-8f2d-4ead-864f-a923936cb5e4 · inbound

Large Language Models Meet Legal Artificial Intelligence: A Survey cites this paper.

Large Language Models Meet Legal Artificial Intelligence: A Survey LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-04T18:26:14.223229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T18:26:14.223229Z digest=sha256:77e4a20c9a2f22d1b413009c89ff8f54cda740c1ee4f8bc4524dcc4d4692b3b1

Observation eddff8e3-83d5-4395-9fd3-9a2b0622ac2b · inbound

TaxPraBen: A Scalable Benchmark for Structured Evaluation of LLMs in Chinese Real-World Tax Practice cites this paper.

TaxPraBen: A Scalable Benchmark for Structured Evaluation of LLMs in Chinese Real-World Tax Practice LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model

Reference 65

Resolution
verified exact
arxiv_id, observed 2026-05-11T05:41:00.782351Z

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.

source=arxiv_source observed=2026-05-10T17:59:44.844149Z digest=sha256:00e0970dc69b6d1882afb8ca9d337c42a3282c6bc350d294bed094de03914224

Observation 67d1eb7f-eed5-4d2f-bc18-5006921e533c · inbound

From Query to Counsel: Structured Reasoning with a Multi-Agent Framework and Dataset for Legal Consultation cites this paper.

From Query to Counsel: Structured Reasoning with a Multi-Agent Framework and Dataset for Legal Consultation LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model

Reference 4

Resolution
malformed identifier
arxiv_id, observed 2026-05-11T09:36:13.098689Z

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.

source=pdf_text observed=2026-05-10T15:54:53.603591Z digest=sha256:53931dbcb94b674fcef7e074fc8c409f72960d719cebb0deef8fe9b74c5f165a

Observation 4bf34098-d542-457d-9032-ea46efde9337 · inbound

Can LLMs Time Travel? Enhancing Temporal Consistency in Legal Agentic Search through Reinforcement Learning cites this paper.

Can LLMs Time Travel? Enhancing Temporal Consistency in Legal Agentic Search through Reinforcement Learning LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model

Reference 5

Resolution
malformed identifier
arxiv_id, observed 2026-06-29T22:14:00.370449Z

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.

source=pdf_text observed=2026-06-29T22:04:47.044235Z digest=sha256:2f80cffb033af783e777f0cb5a0faa65973e1c5e108bb58fc6e4af81e7e4a86f

Observation 635a7d92-d7cb-428b-8d60-ca34b080c3fd · inbound

LLM Evolution as an Industry-Scale Ecosystem: A Lifecycle Perspective on Continual Learning cites this paper.

LLM Evolution as an Industry-Scale Ecosystem: A Lifecycle Perspective on Continual Learning LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model

Reference 144

Resolution
verified exact
arxiv_id, observed 2026-07-03T16:48:39.807777Z

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.

source=pdf_text observed=2026-06-27T05:02:18.347642Z digest=sha256:106d499c2af2c5e96b2164f8a981fdd8a93f988b49717933446beffed57fe30e