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 10 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 10 of 10 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 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:03:48.156445Z

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 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.

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.

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.

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.

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.

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.

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.

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.

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.

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.