Paper Citation Record · LEDGER

LegalAgentBench: Evaluating LLM Agents in Legal Domain

As of 14 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 10 inbound Pith citation observations for arXiv:2412.17259.

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

pith.paper-citation-record.v1
2412.17259 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:43:31.849186Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:55:14.057214Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T06:27:07.348511Z

Reference resolution

36 of 36 outbound references displayed

verified exact1
verified fuzzy0
unresolved35
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3f32d2e7-5539-4033-8d72-be73b897a77a · outbound

This paper cites GPT-4 Technical Report.

LegalAgentBench: Evaluating LLM Agents in Legal Domain GPT-4 Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:30.900150Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e1f35d0-69a9-4887-85be-44c0a58b556b · outbound

This paper cites Qwen Technical Report.

LegalAgentBench: Evaluating LLM Agents in Legal Domain Qwen Technical Report

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:30.967095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af5b9f70-e61b-4f1a-9a53-62ca0258cae4 · outbound

This paper cites an unresolved cited work.

LegalAgentBench: Evaluating LLM Agents in Legal Domain Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-11T05:43:32.649432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1be704f5-7426-4fe1-8650-19990bcc37d4 · outbound

This paper cites PRE: A Peer Review Based Large Language Model Evaluator.

LegalAgentBench: Evaluating LLM Agents in Legal Domain PRE: A Peer Review Based Large Language Model Evaluator

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:30.974094Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a9be135-ac96-415c-99b6-9c1283155d03 · outbound

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

LegalAgentBench: Evaluating LLM Agents in Legal Domain Chatlaw: A Multi-Agent Legal Assistant based on a Role-Aligned Mixture-of-Experts Architecture

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:30.977617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 479e31bf-d38c-498e-a322-cde885df5bab · outbound

This paper cites an unresolved cited work.

LegalAgentBench: Evaluating LLM Agents in Legal Domain Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-11T05:43:32.559261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 02c16e60-00ea-4586-b169-5780ed07ea6c · outbound

This paper cites ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools.

LegalAgentBench: Evaluating LLM Agents in Legal Domain ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:30.984072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f35c2f7-b91c-4403-98ed-ae7e369eb270 · outbound

This paper cites an unresolved cited work.

LegalAgentBench: Evaluating LLM Agents in Legal Domain Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-11T05:43:32.549373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4c483699-7693-414e-bf15-0b1d645a95c1 · outbound

This paper cites MetaTool Benchmark for Large Language Models: Deciding Whether to Use Tools and Which to Use.

LegalAgentBench: Evaluating LLM Agents in Legal Domain MetaTool Benchmark for Large Language Models: Deciding Whether to Use Tools and Which to Use

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:30.989852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 613f0dff-f7c4-4095-bac5-7cab6bf7fdcc · outbound

This paper cites an unresolved cited work.

LegalAgentBench: Evaluating LLM Agents in Legal Domain Unresolved cited work

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:30.993794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aea06b71-c147-48bd-b617-ce29827cde7a · outbound

This paper cites BLADE: Enhancing Black-box Large Language Models with Small Domain-Specific Models.

LegalAgentBench: Evaluating LLM Agents in Legal Domain BLADE: Enhancing Black-box Large Language Models with Small Domain-Specific Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:30.995851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 801376c8-ac76-41ff-af7c-90b8dfd529bb · outbound

This paper cites DELTA: Pre-train a Discriminative Encoder for Legal Case Retrieval via Structural Word Alignment.

LegalAgentBench: Evaluating LLM Agents in Legal Domain DELTA: Pre-train a Discriminative Encoder for Legal Case Retrieval via Structural Word Alignment

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-11T05:43:32.144353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f1c7cc3d-055b-470a-bedb-57d5d2dd1f0a · outbound

This paper cites CalibraEval: Calibrating Prediction Distribution to Mitigate Selection Bias in LLMs-as-Judges.

LegalAgentBench: Evaluating LLM Agents in Legal Domain CalibraEval: Calibrating Prediction Distribution to Mitigate Selection Bias in LLMs-as-Judges

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:31.225208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c5c66cb-cc01-46ea-9e5b-6bd0c05b44ee · outbound

This paper cites LexEval: A Comprehensive Chinese Legal Benchmark for Evaluating Large Language Models.

LegalAgentBench: Evaluating LLM Agents in Legal Domain LexEval: A Comprehensive Chinese Legal Benchmark for Evaluating Large Language Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:31.285636Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b9ce6c4-d32f-4e44-a464-d3e5d793ebd3 · outbound

This paper cites LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods.

LegalAgentBench: Evaluating LLM Agents in Legal Domain LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:31.292630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07961047-b6ca-474b-91c7-3e61428e48cd · outbound

This paper cites an unresolved cited work.

LegalAgentBench: Evaluating LLM Agents in Legal Domain Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-11T05:43:32.537805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c27ae8dd-0cf6-4b0e-98fb-4e7acd8f05f2 · outbound

This paper cites LLM+P: Empowering Large Language Models with Optimal Planning Proficiency.

LegalAgentBench: Evaluating LLM Agents in Legal Domain LLM+P: Empowering Large Language Models with Optimal Planning Proficiency

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:31.302040Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 795af71d-aaa9-45b7-9752-8ac5f06ebe76 · outbound

This paper cites AgentBench: Evaluating LLMs as Agents.

LegalAgentBench: Evaluating LLM Agents in Legal Domain AgentBench: Evaluating LLMs as Agents

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:31.305999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6864b6b7-ed6e-4ab2-a60a-c29b73ed629e · outbound

This paper cites AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents.

LegalAgentBench: Evaluating LLM Agents in Legal Domain AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:31.309052Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4ab7364-f1db-4d79-b34c-0c267e009bd2 · outbound

This paper cites ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs.

LegalAgentBench: Evaluating LLM Agents in Legal Domain ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:31.313784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e48f8d9f-ff08-48c1-8db4-fa30368b36ca · outbound

This paper cites an unresolved cited work.

LegalAgentBench: Evaluating LLM Agents in Legal Domain Unresolved cited work

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:31.317281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34e450d2-43ad-483e-953c-ea7761db7115 · outbound

This paper cites an unresolved cited work.

LegalAgentBench: Evaluating LLM Agents in Legal Domain Unresolved cited work

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:31.365645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce4df773-884a-4634-90be-360e509a2c28 · outbound

This paper cites an unresolved cited work.

LegalAgentBench: Evaluating LLM Agents in Legal Domain Unresolved cited work

Reference 23

Resolution: unresolved; raw_fallback, observed 2026-08-11T05:43:32.384796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1d827b88-f0fb-45cb-893f-d93300fbd135 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

LegalAgentBench: Evaluating LLM Agents in Legal Domain LLaMA: Open and Efficient Foundation Language Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:31.503942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation efb23076-f80c-40cf-9209-d6dff8d6bbe7 · outbound

This paper cites an unresolved cited work.

LegalAgentBench: Evaluating LLM Agents in Legal Domain Unresolved cited work

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:31.507757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9ff3bc8-7345-41c1-a60e-0be86a830765 · outbound

This paper cites Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models.

LegalAgentBench: Evaluating LLM Agents in Legal Domain Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:31.510196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebecddb3-945d-45e6-a4b1-ea7d571f671c · outbound

This paper cites an unresolved cited work.

LegalAgentBench: Evaluating LLM Agents in Legal Domain Unresolved cited work

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:31.513300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a861edd9-5a31-4791-9722-fbb4a400705c · outbound

This paper cites an unresolved cited work.

LegalAgentBench: Evaluating LLM Agents in Legal Domain Unresolved cited work

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:31.517129Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae7bd030-b13d-4cff-a7df-ad3f6b82e1df · outbound

This paper cites an unresolved cited work.

LegalAgentBench: Evaluating LLM Agents in Legal Domain Unresolved cited work

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:31.520911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bcac62ce-7ac9-44f9-b891-19b79a0f44df · outbound

This paper cites React: Synergizing reasoning and acting in language models.

LegalAgentBench: Evaluating LLM Agents in Legal Domain React: Synergizing reasoning and acting in language models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:31.584743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94c24ae8-097f-4274-8bef-f936f6919e11 · outbound

This paper cites ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world Scenarios.

LegalAgentBench: Evaluating LLM Agents in Legal Domain ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world Scenarios

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:31.689503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 079de58c-a35c-4ee8-acdc-7c581a8abcee · outbound

This paper cites BERTScore: Evaluating Text Generation with BERT.

LegalAgentBench: Evaluating LLM Agents in Legal Domain BERTScore: Evaluating Text Generation with BERT

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:31.807563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce05e922-7020-44a4-9fba-b29db2eec050 · outbound

This paper cites A Survey of Large Language Models.

LegalAgentBench: Evaluating LLM Agents in Legal Domain A Survey of Large Language Models

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:31.839524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc687d77-ce4e-437e-9d75-94ca7cb0b8d7 · outbound

This paper cites an unresolved cited work.

LegalAgentBench: Evaluating LLM Agents in Legal Domain Unresolved cited work

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:31.842830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2205a3ba-5b01-4343-8828-c4f9c563aa93 · outbound

This paper cites URL: " 'urlintro :=.

LegalAgentBench: Evaluating LLM Agents in Legal Domain URL: " 'urlintro :=

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:31.845329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d5d1101-085a-4af1-a894-21128cb7e3df · outbound

This paper cites write newline.

LegalAgentBench: Evaluating LLM Agents in Legal Domain write newline

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-11T05:43:31.849186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation ca4500ef-cab4-4921-879b-208520ab91a9 · inbound

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study cites this paper.

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study LegalAgentBench: Evaluating LLM Agents in Legal Domain

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T19:55:14.057214Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1359ade1-72b1-4b74-8a0f-88af0a8f3512 · inbound

From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review cites this paper.

From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review LegalAgentBench: Evaluating LLM Agents in Legal Domain

Reference 105

Resolution: verified exact; arxiv_id, observed 2026-05-15T02:57:38.422719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 01807099-6678-49ed-a9f4-09381aab52d4 · inbound

AppealCase: A Dataset and Benchmark for Civil Case Appeal Scenarios cites this paper.

AppealCase: A Dataset and Benchmark for Civil Case Appeal Scenarios LegalAgentBench: Evaluating LLM Agents in Legal Domain

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T15:03:45.264165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b5fb4e9-c1fb-4fef-982b-9a5323918bb6 · inbound

BenchHub: A Unified Benchmark Suite for Holistic and Customizable LLM Evaluation cites this paper.

BenchHub: A Unified Benchmark Suite for Holistic and Customizable LLM Evaluation LegalAgentBench: Evaluating LLM Agents in Legal Domain

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T12:08:12.933539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2df0fa21-1272-4e55-a493-b1785495c368 · inbound

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation cites this paper.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation LegalAgentBench: Evaluating LLM Agents in Legal Domain

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T11:56:44.927958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c90dfaf9-7314-43e4-902b-b16d313fe0be · inbound

Collaborative Editable Model cites this paper.

Collaborative Editable Model LegalAgentBench: Evaluating LLM Agents in Legal Domain

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-07T00:24:12.928087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2796e88b-1042-4170-a438-d07bc86c1fa6 · inbound

Do LLMs Overthink Basic Math Reasoning? Benchmarking the Accuracy-Efficiency Tradeoff in Language Models cites this paper.

Do LLMs Overthink Basic Math Reasoning? Benchmarking the Accuracy-Efficiency Tradeoff in Language Models LegalAgentBench: Evaluating LLM Agents in Legal Domain

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-19T06:27:07.350996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 45614148-3f14-4d28-ac2e-48f17049ec52 · inbound

LaQual: An Automated Framework for LLM App Quality Evaluation cites this paper.

LaQual: An Automated Framework for LLM App Quality Evaluation LegalAgentBench: Evaluating LLM Agents in Legal Domain

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T16:25:19.244835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54ab8962-1782-4e6a-abc5-c8400e158b9a · inbound

KoBLEX: Open Legal Question Answering with Multi-hop Reasoning cites this paper.

KoBLEX: Open Legal Question Answering with Multi-hop Reasoning LegalAgentBench: Evaluating LLM Agents in Legal Domain

Reference 9474

Resolution: unresolved; no resolver link, observed 2026-08-05T12:46:10.566030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9530e74a-7c18-45c6-abf6-8bb4359c6420 · inbound

ADAM: A Systematic Data Extraction Attack on Agent Memory via Adaptive Querying cites this paper.

ADAM: A Systematic Data Extraction Attack on Agent Memory via Adaptive Querying LegalAgentBench: Evaluating LLM Agents in Legal Domain

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:45:57.687924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.