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Paper Citation Record · LEDGER

LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 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 13 of 13 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 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T10:17:53.688057Z

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 2fd5567e-28aa-43ed-8483-150fb4373594 · inbound

Adapting Network Information into Semantics for Generalizable and Plug-and-Play Multi-Scenario Network Diagnosis cites this paper.

Adapting Network Information into Semantics for Generalizable and Plug-and-Play Multi-Scenario Network Diagnosis LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-10T10:17:53.688057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T10:17:53.688057Z digest=sha256:39970fd306fdf75d12361938dc5340445b085c593df1f6c35490a078bbfc0315

Observation b1c848c2-2e5b-4cf4-b3b1-fadd7a0ef460 · inbound

RTBAgent: A LLM-based Agent System for Real-Time Bidding cites this paper.

RTBAgent: A LLM-based Agent System for Real-Time Bidding LawGPT: A Chinese Legal Knowledge-Enhanced Large Language Model

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-09T17:44:28.510861Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T17:44:28.510861Z digest=sha256:d839c0d8ffc27e843372b5a5ce25f9a56059b7cc0fe84cb9c65d1eb9d4f7b30a

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:cae1ec2375ed75932b84f334ddb1aac832191911e8fedeceb3aad9ee98af5d0c

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:c017708fb8c167b8a0266ab4b7fde42167085fc18d1e55e40e652bf6cfde1fe1

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=sha256:9a7200d155d24b3e948c235febdb4dd97a4715980a07c1f2dd17ccda30d7931a

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=sha256:8b99768a928aef6791ba43011137b5e88f599f31054c610b2df26e3c5d9819ed

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=sha256:1377327024cc8f1ddff5834375a4ac335e68144a49fbb50d0bae569d90a7c8c8

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=sha256:9d222936995e35683e0e096d4622479ee715bf413bc6931ce864213a4809c807

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=sha256:3bc3122f4035ad1ab98913b5646939265d26c0c12b58489fef81442eb17541d5

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

source=arxiv_source observed=2026-05-10T17:59:44.844149Z digest=sha256:8fe78b1e90c9019e2fbc265f3b027a26da4f538e6e7a6027ebfda34ade704013

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

source=pdf_text observed=2026-05-10T15:54:53.603591Z digest=sha256:5f78ea9e78d6469e9c99e62e2a6f9552b93fc1403dca1169c95cc924d00e78e5

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

source=pdf_text observed=2026-06-29T22:04:47.044235Z digest=sha256:72732cad2c868d81895b5b72c8d74bc2777bae8a73d13458066023ad5ef8f1e0

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

source=pdf_text observed=2026-06-27T05:02:18.347642Z digest=sha256:58b59f35458b7c5ef60bc015211309f33afcfc675c54fad2dcb3cbb2006ca4c1