Paper Citation Record · LEDGER

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement

As of 20 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2412.20468.

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

pith.paper-citation-record.v1
2412.20468 v2

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:23:28.680945Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

39 of 39 outbound references displayed

verified exact1
verified fuzzy16
unresolved22
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b2b8e5cd-dbc8-4e01-97ad-261e187cb137 · outbound

This paper cites A Short Survey of Viewing Large Language Models in Legal Aspect.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement A Short Survey of Viewing Large Language Models in Legal Aspect

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T23:23:27.901725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd7f0e03-d631-4b0d-a297-a8ff118a9aeb · outbound

This paper cites To what extent have llms reshaped the legal domain so far? a scoping literature review,.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement To what extent have llms reshaped the legal domain so far? a scoping literature review,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-10T23:23:27.915967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ca721ac-d0ff-460c-bb67-cea8a51a547a · outbound

This paper cites Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T23:23:27.925365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 574ed59e-1029-465d-99ee-e8f3f17fae81 · outbound

This paper cites Cbr-rag: case-based reasoning for retrieval augmented generation in llms for legal question answering,.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement Cbr-rag: case-based reasoning for retrieval augmented generation in llms for legal question answering,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:23:29.919861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 83387b54-4c27-48cd-978a-3cb45cd4ed25 · outbound

This paper cites Ethical framework for harnessing the power of ai in healthcare and beyond,.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement Ethical framework for harnessing the power of ai in healthcare and beyond,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:23:29.872954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4ca0d5a6-24e4-4eed-aad5-c4c2f6a2c91e · outbound

This paper cites A Survey of Hallucination in Large Foundation Models.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement A Survey of Hallucination in Large Foundation Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T23:23:27.958672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0aee7269-c725-4a40-b11d-b509e8ecca72 · outbound

This paper cites Large language models in law: A survey,.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement Large language models in law: A survey,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:23:29.855635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 987d0162-aa8b-42ba-8589-08acdbc88e1b · outbound

This paper cites Language Models are Few-Shot Learners.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement Language Models are Few-Shot Learners

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T23:23:27.990998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8cb8d2e9-ec60-476c-a5c8-b6d89c0330a3 · outbound

This paper cites GPT-4 Technical Report.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement GPT-4 Technical Report

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T23:23:28.023249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9df60e3f-4082-42ec-8bb2-5ef323b4691d · outbound

This paper cites Customizing contextualized language models for legal document reviews,.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement Customizing contextualized language models for legal document reviews,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:23:29.837927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6fb9b1d8-1e00-4ac9-a286-f8c12afc2f6e · outbound

This paper cites LEGAL-BERT: The Muppets straight out of Law School.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement LEGAL-BERT: The Muppets straight out of Law School

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T23:23:28.079520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6a66084-fb5e-4ff7-975d-1d69a38599e0 · outbound

This paper cites Fingpt: Open-source financial large language models,.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement Fingpt: Open-source financial large language models,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T23:23:28.112266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8f0b881-c773-443d-895a-c16e8919ef30 · outbound

This paper cites Medical reports summarization using text-to-text transformer,.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement Medical reports summarization using text-to-text transformer,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:23:29.812694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 79562efb-7a7f-48ea-8b7e-000cae45be9e · outbound

This paper cites DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T23:23:28.172779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af61166a-1e0e-4406-9455-51948adf339e · outbound

This paper cites Chatlaw: A Multi-Agent Legal Assistant based on a Role-Aligned Mixture-of-Experts Architecture.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement Chatlaw: A Multi-Agent Legal Assistant based on a Role-Aligned Mixture-of-Experts Architecture

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T23:23:28.189298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 364c076a-9c07-47e7-9172-5be5d05378ee · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement LoRA: Low-Rank Adaptation of Large Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T23:23:28.210592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b304a58e-f104-4c71-a6f4-f106b4ddbc1c · outbound

This paper cites LexGPT 0.1: pre-trained GPT-J models with Pile of Law.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement LexGPT 0.1: pre-trained GPT-J models with Pile of Law

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-08-10T23:23:29.010863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5d7c0801-a8ea-4cd6-9050-dbe8665c68e9 · outbound

This paper cites Pile of law: Learning responsible data filtering from the law and a 256gb open-source legal dataset,.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement Pile of law: Learning responsible data filtering from the law and a 256gb open-source legal dataset,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:23:29.782961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5922e708-355f-45dc-ab92-2e878296a0dc · outbound

This paper cites Legal Prompting: Teaching a Language Model to Think Like a Lawyer.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement Legal Prompting: Teaching a Language Model to Think Like a Lawyer

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T23:23:28.263305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 463eb2c1-3ff0-4b4e-9944-94f928c031b0 · outbound

This paper cites Can GPT-3 Perform Statutory Reasoning?.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement Can GPT-3 Perform Statutory Reasoning?

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-10T23:23:28.285677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d45dabcf-4094-4341-bab5-6564c71c2681 · outbound

This paper cites A Dataset for Statutory Reasoning in Tax Law Entailment and Question Answering.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement A Dataset for Statutory Reasoning in Tax Law Entailment and Question Answering

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T23:23:28.300776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9075dd9-8214-4c7f-9e61-59e4ef6c9a59 · outbound

This paper cites Tacticalgpt: Uncovering the potential of llms for predicting tactical decisions in professional football,.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement Tacticalgpt: Uncovering the potential of llms for predicting tactical decisions in professional football,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:23:29.751218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6a04e286-7c64-4816-a7a8-022f141e5c29 · outbound

This paper cites Retrieval-augmented generation for knowledge-intensive nlp tasks,.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement Retrieval-augmented generation for knowledge-intensive nlp tasks,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:23:29.706838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b390d89f-ad19-484a-bea9-3e3a72e1fd22 · outbound

This paper cites Simple Is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement Simple Is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T23:23:28.349503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f12479f-b24f-4d90-8a13-23203d7e43c6 · outbound

This paper cites Openagi: When llm meets domain experts,.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement Openagi: When llm meets domain experts,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:23:29.648670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 031edf0d-40f7-46cf-8008-0e598a570e45 · outbound

This paper cites Deep reinforcement learning from human preferences,.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement Deep reinforcement learning from human preferences,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T23:23:28.366343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 694c0e26-618a-4685-a2ff-d991338fd0ee · outbound

This paper cites Answer retrieval in legal community question answering,.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement Answer retrieval in legal community question answering,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:23:29.562221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b48a19cb-0d3f-4d37-a179-6498addb9a16 · outbound

This paper cites When does pretraining help? assessing self-supervised learning for law and the casehold dataset of 53,000+ legal holdings,.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement When does pretraining help? assessing self-supervised learning for law and the casehold dataset of 53,000+ legal holdings,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:23:29.484805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7f2b10e2-780d-4812-8426-d9f5e197206c · outbound

This paper cites Ledgar: A large-scale multi-label cor- pus for text classification of legal provisions in contracts,.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement Ledgar: A large-scale multi-label cor- pus for text classification of legal provisions in contracts,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:23:29.448159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ff7e8f8f-bdfe-4ce3-bca4-deaedaa28773 · outbound

This paper cites Gpt-4 passes the bar exam,.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement Gpt-4 passes the bar exam,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:23:29.428957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 08b7df3e-30e6-46eb-b20e-5d5ddef0db38 · outbound

This paper cites Summary of the compe- tition on legal information, extraction/entailment (coliee) 2023,.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement Summary of the compe- tition on legal information, extraction/entailment (coliee) 2023,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:23:29.402905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6a226271-4d8d-4297-8c86-ee8587717164 · outbound

This paper cites BillSum: A Corpus for Automatic Summarization of US Legislation.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement BillSum: A Corpus for Automatic Summarization of US Legislation

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-10T23:23:28.478405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cea3de57-a3de-4ea4-bbc3-7f4682b23e0e · outbound

This paper cites CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-10T23:23:28.520878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18cca4b6-848d-451e-b1ad-d03c6cc51138 · outbound

This paper cites Super-scotus: A multi-sourced dataset for the supreme court of the us,.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement Super-scotus: A multi-sourced dataset for the supreme court of the us,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:23:29.374895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5c9100b6-fda1-4cbd-8282-46e49a6fb412 · outbound

This paper cites EUR-Lex-Sum: A Multi- and Cross-lingual Dataset for Long-form Summarization in the Legal Domain.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement EUR-Lex-Sum: A Multi- and Cross-lingual Dataset for Long-form Summarization in the Legal Domain

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T23:23:28.583580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b1e9a6a-5d94-4dc8-a835-0ff2e4b02c41 · outbound

This paper cites Neural Legal Judgment Prediction in English.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement Neural Legal Judgment Prediction in English

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-10T23:23:28.589762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2bef294-b248-4bcd-bfae-ae5971e86347 · outbound

This paper cites The Llama 3 Herd of Models.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement The Llama 3 Herd of Models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-10T23:23:28.597527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a20f2a8-d2a0-4593-adc4-723c1b21b755 · outbound

This paper cites Scaling instruction-finetuned language models,.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement Scaling instruction-finetuned language models,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:23:29.345267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 03a1c937-2adc-45be-a919-fcddcd2288c6 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

A Comprehensive Framework for Reliable Legal AI: Combining Specialized Expert Systems and Adaptive Refinement Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-10T23:23:28.680945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.