Pith. sign in

Paper Citation Record · LEDGER

LAiW: A Chinese Legal Large Language Models Benchmark

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2310.05620.

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

pith.paper-citation-record.v1
2310.05620 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:54:25.531241Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T18:37:12.184459Z

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 a0dad2b1-01aa-41fb-a256-7f06387fd6bf · inbound

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

ASP2LJ : An Adversarial Self-Play Laywer Augmented Legal Judgment Framework LAiW: A Chinese Legal Large Language Models Benchmark

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T04:54:25.531241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:54:25.531241Z digest=sha256:650d01cfde0327eab2b4ab62c8f1acdbafd72c4042890dc38a81229138c7f04a

Observation f2603e3e-1ac1-4697-a332-6a6c9211f91e · 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 LAiW: A Chinese Legal Large Language Models Benchmark

Reference 47

Resolution
verified exact
local_arxiv, observed 2026-08-06T18:37:12.187505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T18:37:07.154405Z digest=sha256:d5d81042b1cdea92d33d232b6c4e960cc7fa12df5ef1b6ee468ca8942a35e0f9