Pith. sign in

Paper Citation Record · LEDGER

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

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 32 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 32 of 32 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 32 of 32 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:14:47.100923Z

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

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • 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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-23T23:06:41.081461Z digest=sha256:4a66d4516b32139e804711ce8b58612a2c671775361203dad15cfed8b93f1ece

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-23T02:18:27.204122Z digest=sha256:0963589850c46503203b210795a00771180c501f837e3e028a6a85d9d6a86f06

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-22T17:53:42.369128Z digest=sha256:f9673a23413d1bee2bdb5402c5aef7aa5216da32c3d788916ef1c54dcdeeeb97

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=sha256:3a1c7d85af1bfa4e49d6cd89638afec9f93ac27efc76eb715b572687b66af3d6

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=sha256:570461dd5ee0e0dff509a7a42b0cedf8ecbaa0f0c0386d539bd7e4d8dc131244

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=sha256:8f5070a6e7047367b41d2e3ed1efc8a3af47b8dbf6386b5147232e601fdf7209

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-08T11:55:29.109903Z digest=sha256:a5ae320290e96db763f04312325d708f3b8880fb82e64db8032ea07f50f50826

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-07T16:12:59.901188Z digest=sha256:aa3de9bafb4bc8a839139b24e183d199562a8ca4a075bfaddf470424575d1dbc

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-09T14:22:11.383735Z digest=sha256:de06c8064121fa15d49be5633caae480904bb0e79fe5b0c700afaca66eef57ba

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T02:09:15.827929Z digest=sha256:799824cff39f0e600496076f14ddff895a156edcb2ad6ed467612d0bd8d2f78b

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-21T05:10:25.633567Z digest=sha256:f876c04e02db39d65bc7ea126d4662d31f4f4a1280025897c8556489dc7c5aac

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-22T09:43:17.040131Z digest=sha256:d861d548da60386c4ef8889c8261cab78992ce2ebf7f2d66ef6e3cf8041e31fe

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-25T05:54:45.589083Z digest=sha256:c652d98d897c8cf25b8d9ad37f3996ab2a08d475e381a9bd68d832f37ffad7a1

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-29T16:36:09.830236Z digest=sha256:d23b2bc29f0f2dc0f1bb475248c0557613b51d538b661abec5afc48f7dcc923f

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-29T05:13:07.747936Z digest=sha256:392999aa1270d269050fcb59dafafb4d202846af81f2745faebabf4cc6eb916d

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-29T07:37:36.187564Z digest=sha256:58e38bd111b075e982a91e23a1e3840845fa3206783ceb77c060cf7ca09108b2

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-28T08:39:28.510255Z digest=sha256:5468ce4e255603f26b6b997677111927cf64b5a6043dc2f65815271de4c3a0a9

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-28T10:35:11.989106Z digest=sha256:8c837f1272f2d7ec81950dde05a5894a9d73b6fa6ae762a8c1f31eb9aadf2f20

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-26T22:26:54.239505Z digest=sha256:7fbb75026e6cdba78a5cf94e08dc6a40c980dda8ca7f5add3a34a3046d9b1188

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

Resolution
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

Resolution
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

Resolution
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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T01:34:36.960263Z digest=sha256:c9dec830a2cef61d52eaa77ab09fd0df59b0dd8d4d0ec46f8d1397161b719c42