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Paper Citation Record · LEDGER

LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 33 inbound Pith citation observations for arXiv:2408.10343.

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

pith.paper-citation-record.v1
2408.10343 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 33 of 33 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 33 of 33 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T19:15:25.480485Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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  • metadata mismatch0

External citation measurements

7
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e8e1279e-a2b5-472a-a277-c45ee79e063e · inbound

Retrieval-Augmented Generation for Natural Language Processing: A Survey cites this paper.

Retrieval-Augmented Generation for Natural Language Processing: A Survey LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 138

Resolution
verified exact
arxiv_id, observed 2026-05-23T23:08:35.530939Z

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=2026-05-23T23:06:41.081461Z digest=sha256:c9bdd40da89856e5d0ec0f3ba548916fa959fb51c13fa19f2a0f0f518430f964

Observation a87b0599-b09c-4814-9e29-4f3e680b5420 · inbound

Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey cites this paper.

Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 138

Resolution
unresolved
no resolver link, observed 2026-08-08T19:15:25.480485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T19:15:25.480485Z digest=sha256:8b6f98e3db54bc82914a402a68190c5ecd7f346dd2ea80a1ec341c3b6007db75

Observation 09e88e00-81f4-463e-8ade-d3cd147980a3 · inbound

Supervising the search process produces reliable and generalizable information-seeking agents cites this paper.

Supervising the search process produces reliable and generalizable information-seeking agents LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 53

Resolution
metadata mismatch
arxiv_id, observed 2026-05-23T02:22:25.411929Z

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=2026-05-23T02:18:27.204122Z digest=sha256:b435231c3be2efcbb74923b3982082291fe086161d37be9bcbfaa931e2946b1d

Observation b80ca526-c80a-467d-aedc-2c6e288b2bb6 · inbound

An Ontology-Driven Graph RAG for Legal Norms: A Structural, Temporal, and Deterministic Approach cites this paper.

An Ontology-Driven Graph RAG for Legal Norms: A Structural, Temporal, and Deterministic Approach LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 6

Resolution
metadata mismatch
arxiv_id, observed 2026-05-22T17:55:01.758880Z

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=2026-05-22T17:53:42.369128Z digest=sha256:57e690d1c6c11eb2f01367d4280a75e614462962138595e36160702624a70be1

Observation 06a65c60-3484-4980-ba3a-55c9fcf0124f · inbound

Ranking Free RAG: Replacing Re-ranking with Selection in RAG for Sensitive Domains cites this paper.

Ranking Free RAG: Replacing Re-ranking with Selection in RAG for Sensitive Domains LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T15:14:47.100923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:14:47.100923Z digest=sha256:1f6ee5e42c554cdd4d11644fbe4bc525bf34047905109295072a8a1c4b3782a7

Observation 3a5d7094-c8ae-4d5b-a75c-3ba07ab1dd5b · inbound

Hypercube-Based Retrieval-Augmented Generation for Scientific Question-Answering cites this paper.

Hypercube-Based Retrieval-Augmented Generation for Scientific Question-Answering LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T14:21:56.048460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:21:56.048460Z digest=sha256:5f0c25469730c0697ee0d7fb431f3ba0a049aa258c18ade574af80818b43983e

Observation 0361649b-351f-4512-9fa8-13d79663f0ef · inbound

Can Compressed LLMs Truly Act? An Empirical Evaluation of Agentic Capabilities in LLM Compression cites this paper.

Can Compressed LLMs Truly Act? An Empirical Evaluation of Agentic Capabilities in LLM Compression LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T14:17:57.261092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:57.261092Z digest=sha256:e494e4d03ff4d7493ebcc5466eabac53f38d85deefc62425ef971c357abcabd8

Observation ada1333a-fc42-4d91-8b3a-e65768243590 · inbound

CPA-RAG:Covert Poisoning Attacks on Retrieval-Augmented Generation in Large Language Models cites this paper.

CPA-RAG:Covert Poisoning Attacks on Retrieval-Augmented Generation in Large Language Models LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T14:10:28.231858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:10:28.231858Z digest=sha256:30298917df4cb705f826c84ef4197f28e93dfd51db9d4aeea95c1db190e0c871

Observation 18e5eb42-7114-43be-aef7-8dfc6032a0f5 · inbound

On Path to Multimodal Historical Reasoning: HistBench and HistAgent cites this paper.

On Path to Multimodal Historical Reasoning: HistBench and HistAgent LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T14:01:16.313186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:01:16.313186Z digest=sha256:68e618169bd9190e9aedf033deeafbb8d95ee6f36452eb0ccda3e22b1a90eb66

Observation ba53a88f-d572-48db-8ca4-2f21275002e6 · inbound

RAG-Zeval: Towards Robust and Interpretable Evaluation on RAG Responses through End-to-End Rule-Guided Reasoning cites this paper.

RAG-Zeval: Towards Robust and Interpretable Evaluation on RAG Responses through End-to-End Rule-Guided Reasoning LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T13:14:31.960278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:14:31.960278Z digest=sha256:a8096539797bd44aa7427ac17444918ae74f0b20bf7ebc9ecef2d876390f0b8f

Observation f8ad1e76-cbb3-40b0-b5ca-801011f39d01 · inbound

Position: Text Embeddings Should Capture Implicit Semantics, Not Just Surface Meaning cites this paper.

Position: Text Embeddings Should Capture Implicit Semantics, Not Just Surface Meaning LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 79

Resolution
unresolved
no resolver link, observed 2026-08-07T05:18:28.086107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:18:28.086107Z digest=sha256:8f3218379150c358d79203e757a56eaf5e68d7bab303a4f785d652c8ca363148

Observation 024b5934-0914-4556-b5e8-93d45c241c1b · inbound

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

ASP2LJ : An Adversarial Self-Play Laywer Augmented Legal Judgment Framework LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T04:54:27.490816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:54:27.490816Z digest=sha256:b272bcbcf9ce0acab54851e60c529d678126b611062d8896ad479511731c335a

Observation 277d8749-cf37-41aa-b518-3ee3e64efcfe · inbound

From Query to Explanation: Uni-RAG for Multi-Modal Retrieval-Augmented Learning in STEM cites this paper.

From Query to Explanation: Uni-RAG for Multi-Modal Retrieval-Augmented Learning in STEM LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-06T20:05:45.415601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:05:45.415601Z digest=sha256:7c8edee111ea2928cabaaaa48cd289c34ac41720f9affd37a6814dc098948115

Observation cea246d1-1066-40f9-b662-d124c54ce514 · inbound

AI for Statutory Simplification: A Comprehensive State Legal Corpus and Labor Benchmark cites this paper.

AI for Statutory Simplification: A Comprehensive State Legal Corpus and Labor Benchmark LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-05T15:51:46.366040Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:51:46.366040Z digest=sha256:49bd4f7334bcd961e7c6a0052c3ecc50c40b29a642b58cc2d6df339ace156d04

Observation e5fd3d4f-5ad2-4736-b10c-612ea15e0eb7 · inbound

SAMVAD: A Multi-Agent System for Simulating Judicial Deliberation Dynamics in India cites this paper.

SAMVAD: A Multi-Agent System for Simulating Judicial Deliberation Dynamics in India LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-05T10:42:48.460862Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:42:48.460862Z digest=sha256:109f7bd019a81492214e2bcf2bb28b734d6ec5f9b63e5a9a0ad6a4a87ce89374

Observation b34bb446-fa3f-494a-9b16-48aad10aac11 · inbound

ReLeVAnT: Relevance Lexical Vectors for Accurate Legal Text Classification cites this paper.

ReLeVAnT: Relevance Lexical Vectors for Accurate Legal Text Classification LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 7

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T19:26:09.964423Z

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=2026-05-08T11:55:29.109903Z digest=sha256:86f6a8c35273766e9489565fe571e02d4ab02a67d5ac20f93d5859ad5800a61c

Observation 1af13f5d-5c89-43d3-a510-25ded8e91f94 · inbound

Navigating Global AI Regulation: A Multi-Jurisdictional Retrieval-Augmented Generation System cites this paper.

Navigating Global AI Regulation: A Multi-Jurisdictional Retrieval-Augmented Generation System LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 58

Resolution
verified exact
arxiv_id, observed 2026-05-11T23:51:17.005824Z

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=2026-05-07T16:12:59.901188Z digest=sha256:b09a729fd8120a783d23bf25dc2c5031bcc1c336717f41fc299c689528a9f3bd

Observation a9142b29-c656-4b69-a252-b5bf245d0bca · inbound

MAP-Law: Coverage-Driven Retrieval Control for Multi-Turn Legal Consultation cites this paper.

MAP-Law: Coverage-Driven Retrieval Control for Multi-Turn Legal Consultation LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 11

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T16:56:09.222386Z

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=2026-05-09T14:22:11.383735Z digest=sha256:1b8716404070ccfe34ea8bc339d2ea99bcf8567f7ac139c77567e9989f879e0b

Observation a9465178-10ce-4b9f-adf4-a0a618aeebca · inbound

Deepchecks: Evaluating Retrieval-Augmented Generation (RAG) cites this paper.

Deepchecks: Evaluating Retrieval-Augmented Generation (RAG) LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 11

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T02:09:38.732291Z

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=2026-05-15T02:09:15.827929Z digest=sha256:ada885851d2de4569bbd7afb588ecfeeda84e652eb37d3ed6c93233380965235

Observation bd3ee14f-1bfd-4e31-a1e3-71b40de3c78b · inbound

Fine-grained Claim-level RAG Benchmark for Law cites this paper.

Fine-grained Claim-level RAG Benchmark for Law LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-21T05:13:58.094169Z

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=2026-05-21T05:10:25.633567Z digest=sha256:89229ed596d5fdca924bfeba47629f803dc2ec40caa570f3a0f36da16ef9e0e2

Observation 3784f1e6-df54-4cdf-a9af-a79c70129ba9 · inbound

Fine-grained Claim-level RAG Benchmark for Law cites this paper.

Fine-grained Claim-level RAG Benchmark for Law LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-22T09:44:45.811789Z

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=2026-05-22T09:43:17.040131Z digest=sha256:184ab424f728ec9136a5d9ebe785e6e8a4f51a817c8f6530d7f9fbf3cddb5f5c

Observation df5948b5-7218-4326-8d93-8fb6a0450244 · inbound

Fine-grained Claim-level RAG Benchmark for Law cites this paper.

Fine-grained Claim-level RAG Benchmark for Law LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:55:22.953570Z

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=2026-05-25T05:54:45.589083Z digest=sha256:d52c6b74337eb0cef8c0d0e064d56b2d5aba84f2b7e35d1317b7022532c23cff

Observation acacabb9-418f-4f2f-981d-5de6cbec6fd3 · inbound

Maat: The Agentic Legal Research Assistant for Competition Protection cites this paper.

Maat: The Agentic Legal Research Assistant for Competition Protection LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-06-29T16:53:41.450365Z

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=2026-06-29T16:36:09.830236Z digest=sha256:86c7853713526f1b9bcc4df844d918b94b2e31fb7b80444a50585074a619132b

Observation de62d7d1-31f2-4c5d-b1de-170dade1a26e · inbound

LexPath: A domain-oriented multi-path framework for legal article retrieval cites this paper.

LexPath: A domain-oriented multi-path framework for legal article retrieval LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T18:13:49.350887Z

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=2026-06-29T05:13:07.747936Z digest=sha256:918ab26b9926c70c01986cca0b1e33dda7025ccf2248e263cbcecd10cfec2246

Observation 6a02a7d3-ea34-45a9-a0aa-9b3a25f32832 · inbound

CanLegalRAGBench: Evaluating Retrieval-Augmented Generation on Canadian Case Law cites this paper.

CanLegalRAGBench: Evaluating Retrieval-Augmented Generation on Canadian Case Law LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 2

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T07:43:13.872758Z

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=2026-06-29T07:37:36.187564Z digest=sha256:3329a6345c772a60f74196298b7339077c6e6c67e6951953a9cb358917c69cfb

Observation 738448c5-3850-40a1-af97-1e18c9d2d6e8 · inbound

Section-Weighted Hybrid Approach for Legal Case Retrieval cites this paper.

Section-Weighted Hybrid Approach for Legal Case Retrieval LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 9

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T04:56:39.304942Z

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=2026-06-28T08:39:28.510255Z digest=sha256:460360b72b63e7393c97127ae16f8b542c1fd1d131f7ce61ab39a658c266b1ee

Observation 3b8f5086-830b-4014-af60-ce370a7025cf · inbound

Re-Ranking Through an Attribution Lens for Citation Quality in Legal QA cites this paper.

Re-Ranking Through an Attribution Lens for Citation Quality in Legal QA LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-07-02T02:46:29.363120Z

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=2026-06-28T10:35:11.989106Z digest=sha256:851741a98daf3ac4bc927d79286d72d5f1ec5b2d27299b20063385a660810e8c

Observation 50ecc0c9-0b65-40da-bf46-11b39a0f535a · inbound

Legal Reasoning Is Not Lawyering: Rethinking Legal Benchmarks for Pro Se Access to Justice cites this paper.

Legal Reasoning Is Not Lawyering: Rethinking Legal Benchmarks for Pro Se Access to Justice LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T23:19:03.968034Z

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=arxiv_source observed=2026-06-26T22:26:54.239505Z digest=sha256:4a81b873da23f18781525620f4d592834e0f71e494ee000d96b3487d5049bd24

Observation 8cd400e2-3620-4a32-9b1a-734fc79f9bef · inbound

NormWorlds-CF: Solver-Verified Counterfactual Normative Reasoning with Metamorphic-Relation GRPO cites this paper.

NormWorlds-CF: Solver-Verified Counterfactual Normative Reasoning with Metamorphic-Relation GRPO LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 23

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unresolved
no resolver link, observed 2026-07-11T22:45:47.429470Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T22:45:47.429470Z digest=sha256:fdf10262c77b8c46cb633acce598b91db06dc6fa6ceb65b13204702927852157

Observation 49a46a8d-9ea8-49f3-8f94-dc1f0642181a · inbound

NormWorlds-CF: Solver-Verified Counterfactual Normative Reasoning with Metamorphic-Relation GRPO cites this paper.

NormWorlds-CF: Solver-Verified Counterfactual Normative Reasoning with Metamorphic-Relation GRPO LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-02T08:49:45.645687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T08:49:45.645687Z digest=sha256:7fc7e8916e7f6903c3b88b2b31e87304d56ebb36109831ad16c7d8b176eb962c

Observation b59db531-16e1-4e12-a0f6-4dcb096afe17 · inbound

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval cites this paper.

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 16

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unresolved
no resolver link, observed 2026-08-02T08:58:42.760654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T08:58:42.760654Z digest=sha256:019126e4e8d499910cb5d748e4262d8ed9899a4649a25d966d34615ee85bdbc7

Observation ac36cedb-959a-4439-8d2a-3e91b7b25d52 · inbound

Evaluating RAG for French immigration law: a benchmark and baseline study cites this paper.

Evaluating RAG for French immigration law: a benchmark and baseline study LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 14

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unresolved
no resolver link, observed 2026-07-31T14:41:31.365626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T14:41:31.365626Z digest=sha256:6ab3b8166f396f98045232be5dc2e5f391dea85e690fc257b048394424532ec8

Observation 7faeaff8-c8a3-4a02-8bf9-17cb02f77960 · inbound

RAG-TESTER: Automated End-to-End Testing of Retrieval-Augmented Large Language Models cites this paper.

RAG-TESTER: Automated End-to-End Testing of Retrieval-Augmented Large Language Models LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 4

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unresolved
no resolver link, observed 2026-08-04T01:34:36.960263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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