Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2306.09525.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T19:58:04.132162Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-19T11:52:16.245390Z
0 of 0 outbound references displayed
External citation measurements
No source-named external measurement is stored.
No outbound reference observations are available for this paper version.
Observation 669e86d0-28e8-4c82-a4b7-8fac32fa1d4f · inbound
Legal Evalutions and Challenges of Large Language Models Explaining Legal Concepts with Augmented Large Language Models (GPT-4)
Reference 34
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5844d97b-8016-45f4-8290-a00f40685596 · inbound
From Lived Experience to Insight: Unpacking the Psychological Risks of Using AI Conversational Agents Explaining Legal Concepts with Augmented Large Language Models (GPT-4)
Reference 82
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4f85bd35-11c3-40ca-8537-99757ea59d44 · inbound
CitaLaw: Enhancing LLM with Citations in Legal Domain Explaining Legal Concepts with Augmented Large Language Models (GPT-4)
Reference 9
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 31509cc2-a7b7-49de-9483-61268ae8df90 · inbound
Analyzing Images of Legal Documents: Toward Multi-Modal LLMs for Access to Justice Explaining Legal Concepts with Augmented Large Language Models (GPT-4)
Reference 29
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a684dc70-65ce-4457-9c8d-89511fc5230e · inbound
Automating Legal Interpretation with LLMs: Retrieval, Generation, and Evaluation Explaining Legal Concepts with Augmented Large Language Models (GPT-4)
Reference 2023
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a77c2ff1-9c92-4830-9fbc-91b894cc109e · inbound
From Standalone LLMs to Integrated Intelligence: A Survey of Compound Al Systems Explaining Legal Concepts with Augmented Large Language Models (GPT-4)
Reference 151
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation d3aee48d-a61a-49a3-8507-578989ec3f3c · inbound
LePREC: Reasoning as Classification over Structured Factors for Assessing Relevance of Legal Issues Explaining Legal Concepts with Augmented Large Language Models (GPT-4)
Reference 4
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 61db5d67-ae80-4405-a699-9faa5b0e7f8d · inbound
Evaluating RAG for French immigration law: a benchmark and baseline study Explaining Legal Concepts with Augmented Large Language Models (GPT-4)
Reference 16
Source-reported events for the cited work
Unavailable: canonical work link unavailable.