Paper Citation Record · LEDGER

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation

As of 8 August 2026, this Paper Citation Record lists 65 of 65 outbound references and 1 inbound Pith citation observation for arXiv:2505.14015.

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

pith.paper-citation-record.v1
2505.14015 v2

Coverage vector

measured 65 of 65 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:44:37.677071Z

measured 66 of 66 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T12:35:01.443896Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T12:36:22.403104Z

Reference resolution

65 of 65 outbound references displayed

verified exact2
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7247335d-0a82-4454-8469-7e9926dac2e0 · outbound

This paper cites an unresolved cited work.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Unresolved cited work

Reference 1

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Observation 21600819-baf9-4222-9606-81667b550237 · outbound

This paper cites Unfair TOS: An Automated Approach using Customized BERT.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Unfair TOS: An Automated Approach using Customized BERT

Reference 2

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Observation 4cbb8d18-334c-4cfa-b7d3-055e1aad1876 · outbound

This paper cites Rapid transit systems regulations, 2025.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Rapid transit systems regulations, 2025

Reference 3

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This paper cites What Will it Take to Fix Benchmarking in Natural Language Understanding?.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation What Will it Take to Fix Benchmarking in Natural Language Understanding?

Reference 4

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Observation 9eff350c-e871-4cf4-a973-51740675abac · outbound

This paper cites Neural Legal Judgment Prediction in English.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Neural Legal Judgment Prediction in English

Reference 5

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Observation 40066a09-8f97-48ab-ac11-cbd7d673c1c1 · outbound

This paper cites Paragraph-level Rationale Extraction through Regularization: A case study on European Court of Human Rights Cases.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Paragraph-level Rationale Extraction through Regularization: A case study on European Court of Human Rights Cases

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T15:44:29.974848Z

Source-reported events for the cited work

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Observation a7928929-4296-4728-9bb8-d57fbb986c17 · outbound

This paper cites LexGLUE: A Benchmark Dataset for Legal Language Understanding in English.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation LexGLUE: A Benchmark Dataset for Legal Language Understanding in English

Reference 7

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Observation 950002e5-3780-484f-8a98-17966edb49ca · outbound

This paper cites Chang, X.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Chang, X

Reference 8

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This paper cites Chase and L.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Chase and L

Reference 9

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Observation 4fe2844c-a3f1-4679-9638-2417c3fd5176 · outbound

This paper cites Universal Self-Consistency for Large Language Model Generation.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Universal Self-Consistency for Large Language Model Generation

Reference 10

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Observation e056dbd0-85da-46de-ab5f-96d6ac8cc78b · outbound

This paper cites Cheng, S.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Cheng, S

Reference 11

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Unresolved cited work

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Observation b8c75ba4-7a99-4926-8730-fd1a3e120c51 · outbound

This paper cites DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs

Reference 13

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This paper cites Model Editing Harms General Abilities of Large Language Models: Regularization to the Rescue.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Model Editing Harms General Abilities of Large Language Models: Regularization to the Rescue

Reference 14

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Unresolved cited work

Reference 15

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Observation f3e4343d-ce68-4aaf-b888-a46e546e6a76 · outbound

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Unresolved cited work

Reference 16

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Observation d12764bc-068e-4d6b-b48e-4ce9e13ea709 · outbound

This paper cites COMPL-AI Framework: A Technical Interpretation and LLM Benchmarking Suite for the EU Artificial Intelligence Act.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation COMPL-AI Framework: A Technical Interpretation and LLM Benchmarking Suite for the EU Artificial Intelligence Act

Reference 17

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Model Editing at Scale leads to Gradual and Catastrophic Forgetting

Reference 18

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation A Unified Framework for Model Editing

Reference 19

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Don't Stop Pretraining: Adapt Language Models to Domains and Tasks

Reference 20

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Hartvigsen, S

Reference 21

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation ORPO: Monolithic Preference Optimization without Reference Model

Reference 22

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation AI safety via debate

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Jiang, Y

Reference 24

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Unresolved cited work

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Observation 06e93608-3a79-4d69-bf07-c0063b1a6d72 · outbound

This paper cites Debating with More Persuasive LLMs Leads to More Truthful Answers.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Debating with More Persuasive LLMs Leads to More Truthful Answers

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Self-Generated In-Context Learning: Leveraging Auto-regressive Language Models as a Demonstration Generator

Reference 27

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Kojima, S

Reference 28

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Unresolved cited work

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This paper cites Should We Really Edit Language Models? On the Evaluation of Edited Language Models.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Should We Really Edit Language Models? On the Evaluation of Edited Language Models

Reference 30

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation PMET: Precise Model Editing in a Transformer

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Making Large Language Models Better Reasoners with Step-Aware Verifier

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Chain-of-Dictionary Prompting Elicits Translation in Large Language Models

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Tree of Attacks: Jailbreaking Black-Box LLMs Automatically

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Unresolved cited work

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Unresolved cited work

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Debate Helps Supervise Unreliable Experts

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Mitchell, C

Reference 38

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation UniAdapt: A Universal Adapter for Knowledge Calibration

Reference 39

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Ouyang, J

Reference 40

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Red Teaming Language Models with Language Models

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Measuring and Narrowing the Compositionality Gap in Language Models

Reference 42

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Rafailov, A

Reference 43

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Rafailov, A

Reference 44

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Selective Annotation Makes Language Models Better Few-Shot Learners

Reference 46

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Tuggener, P

Reference 48

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Soft Self-Consistency Improves Language Model Agents

Reference 49

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Cue-CoT: Chain-of-thought Prompting for Responding to In-depth Dialogue Questions with LLMs

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Boosting Language Models Reasoning with Chain-of-Knowledge Prompting

Reference 51

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This paper cites A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 52

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Observation 6a989074-efb8-44ee-8131-38bff7cd2341 · outbound

This paper cites WISE: Rethinking the Knowledge Memory for Lifelong Model Editing of Large Language Models.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation WISE: Rethinking the Knowledge Memory for Lifelong Model Editing of Large Language Models

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-07T15:44:36.184817Z

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Observation fc5e7b5c-f91e-47ac-8787-fdc987607890 · outbound

This paper cites LEMoE: Advanced Mixture of Experts Adaptor for Lifelong Model Editing of Large Language Models.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation LEMoE: Advanced Mixture of Experts Adaptor for Lifelong Model Editing of Large Language Models

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T15:44:36.284825Z

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Observation 216b3c8a-152f-448f-90c2-11b557709b73 · outbound

This paper cites MEMoE: Enhancing Model Editing with Mixture of Experts Adaptors.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation MEMoE: Enhancing Model Editing with Mixture of Experts Adaptors

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T15:44:36.382919Z

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Observation a54f0538-afc4-4b09-9a25-277f5d15e0bf · outbound

This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-07T15:44:36.534881Z

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Observation 8eebfd99-b86f-4f24-845c-3a3b109725dc · outbound

This paper cites AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T15:44:36.671264Z

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Observation 95f54e3b-6556-475f-9b43-978d43070305 · outbound

This paper cites Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-07T15:44:36.826281Z

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Observation de37bb04-3c96-47a9-b531-94c6eba97a24 · outbound

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Unresolved cited work

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T15:44:36.904818Z

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Observation 3c102c70-b362-44a0-a9f1-7449abaddfb7 · outbound

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-07T15:44:37.034806Z

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Observation 45bdeb3b-2812-481b-8b48-28e4a965848e · outbound

This paper cites an unresolved cited work.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Unresolved cited work

Reference 61

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Observation 8942558c-693d-41d1-93c8-aa22b577bdf6 · outbound

This paper cites Automatic Chain of Thought Prompting in Large Language Models.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Automatic Chain of Thought Prompting in Large Language Models

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T15:44:37.360605Z

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Observation 7d11f460-af10-4a1d-9ed5-1dc11ca9e0de · outbound

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AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation ALI-Agent: Assessing LLMs' Alignment with Human Values via Agent-based Evaluation

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-07T15:44:37.514951Z

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Observation db94feb9-7413-4a1c-89ae-4fb608dcd4f1 · outbound

This paper cites Jason eats a burger on train.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Jason eats a burger on train

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:44:42.874304Z

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Observation 03a6f583-5513-4f88-a652-13be331d70f5 · outbound

This paper cites an unresolved cited work.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation Unresolved cited work

Reference 2023

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:44:44.943445Z

Source-reported events for the cited work

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Pith citing papers

Observation 9087ef2b-6f19-42b1-8924-78895d26c02e · inbound

AgenticEval: Toward Agentic and Self-Evolving Safety Evaluation of Large Language Models cites this paper.

AgenticEval: Toward Agentic and Self-Evolving Safety Evaluation of Large Language Models AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-18T12:36:22.406321Z

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