Paper Citation Record · LEDGER

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval

As of 17 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 1 inbound Pith citation observation for arXiv:2509.00141.

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

pith.paper-citation-record.v1
2509.00141 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T13:58:41.813819Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T17:36:30.486056Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T03:49:30.527669Z

Reference resolution

25 of 25 outbound references displayed

verified exact0
verified fuzzy15
unresolved8
parse uncertain0
malformed identifier2
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1a73e09d-5db1-4b2a-b128-6e810082d8c4 · outbound

This paper cites Data-centric and logic-based models for automated legal problem solving,.

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval Data-centric and logic-based models for automated legal problem solving,

Reference 2

Resolution: malformed identifier; no resolver link, observed 2026-08-05T13:58:39.344826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ebc22a9-2f07-47ad-a084-1372a464c1d1 · outbound

This paper cites an unresolved cited work.

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-05T13:58:45.648820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation dc44ea6d-d044-4c23-b4d0-83e90a09ad28 · outbound

This paper cites Legislative updates in the digital era,.

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval Legislative updates in the digital era,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:58:45.476737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 135474e8-8347-445e-8f29-0cde008aae81 · outbound

This paper cites Taxman: An experiment in artificial intelligence and legal reasoning,.

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval Taxman: An experiment in artificial intelligence and legal reasoning,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:58:45.333649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3969f87b-8043-4a1e-925e-cd1ac1e38e51 · outbound

This paper cites Hypo: A case-based reasoning system for argumentation,.

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval Hypo: A case-based reasoning system for argumentation,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:58:45.139372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8257b184-7c60-45ff-bc2c-a0b1a77f86e7 · outbound

This paper cites an unresolved cited work.

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval Unresolved cited work

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T13:58:39.806515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca7e88af-830f-44ba-8ebf-eb0fc63181c5 · outbound

This paper cites Machine learning in legal document classification,.

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval Machine learning in legal document classification,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:58:44.783955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 300da0b7-f5f7-4122-989f-366dc69d42b2 · outbound

This paper cites Semantic retrieval of legal documents,.

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval Semantic retrieval of legal documents,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:58:44.417356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 484fd85b-6572-44ac-a2a3-ce978331927a · outbound

This paper cites Predictive analytics and law: Models, outcomes, and fairness,.

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval Predictive analytics and law: Models, outcomes, and fairness,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:58:44.047828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6ca8479e-f7ee-4fa3-b45b-552453c64c7a · outbound

This paper cites Tetlock, Expert Political Judgment: How Good Is It? Princeton University Press, 2007.

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval Tetlock, Expert Political Judgment: How Good Is It? Princeton University Press, 2007

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:58:43.864757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9c08c81f-4ae2-457c-b660-3a80193e20dc · outbound

This paper cites Attention is all you need,.

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval Attention is all you need,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:58:43.567277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 031527c5-0446-447d-88bd-5f4dda67df3a · outbound

This paper cites A general approach for predicting the behavior of the supreme court of the united states,.

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval A general approach for predicting the behavior of the supreme court of the united states,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T13:58:40.371257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51de8d5a-d947-4bc2-9604-1749c2ab9691 · outbound

This paper cites Legal summarization models and their practical performance,.

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval Legal summarization models and their practical performance,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:58:43.380039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0db1c2c6-5031-49c1-bd35-56b82089d3b5 · outbound

This paper cites Predicting judicial decisions of the european court of human rights: A natural language processing perspective,.

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval Predicting judicial decisions of the european court of human rights: A natural language processing perspective,

Reference 15

Resolution: malformed identifier; no resolver link, observed 2026-08-05T13:58:40.563679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66808251-2253-4f95-b9b7-cf1ae15b3cdd · outbound

This paper cites Longformer: The Long-Document Transformer.

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval Longformer: The Long-Document Transformer

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T13:58:40.854590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b4aa4aa-3160-42fd-98e2-4e4e274caa0f · outbound

This paper cites Big bird: Transformers for longer sequences,.

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval Big bird: Transformers for longer sequences,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:58:43.191277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 65df7100-3749-4739-9ec3-a26dafd2faa1 · outbound

This paper cites Combining Recurrent, Convolutional, and Continuous-time Models with Linear State-Space Layers.

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval Combining Recurrent, Convolutional, and Continuous-time Models with Linear State-Space Layers

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-05T13:58:41.056169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af1d85df-ce5c-43bf-8796-378e061f8ab0 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-05T13:58:41.146371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2198b508-4c5c-415b-ad8b-63c8014bbec7 · outbound

This paper cites Benchmarking mamba’s document ranking performance on legal data,.

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval Benchmarking mamba’s document ranking performance on legal data,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:58:43.008524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1bf5b9ce-5959-4517-992c-6062a0772110 · outbound

This paper cites Mamba explained—a potential replacement for transform- ers,.

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval Mamba explained—a potential replacement for transform- ers,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:58:42.830380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 42029739-62f4-4892-8c1e-b800dc0dcea1 · outbound

This paper cites Legal-bert: The muppets straight out of law school,.

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval Legal-bert: The muppets straight out of law school,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:58:42.642948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b8b8f2a1-bee9-4250-8639-1c0ea812ba47 · outbound

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

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval LexGLUE: A Benchmark Dataset for Legal Language Understanding in English

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-05T13:58:41.573359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd0be482-0864-44b2-8e8c-fe3746a40c6d · outbound

This paper cites The open case law project: Open data for legal ai benchmarking,.

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval The open case law project: Open data for legal ai benchmarking,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:58:42.473960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b92be021-7ec2-4159-a434-97cec1dec402 · outbound

This paper cites Benchmarking the ability of large language models to ground legal reasoning in statutory text,.

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval Benchmarking the ability of large language models to ground legal reasoning in statutory text,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T13:58:42.279806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8561d914-bd5d-4a0e-99f5-e9ab12542117 · outbound

This paper cites Generating Long Sequences with Sparse Transformers.

Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval Generating Long Sequences with Sparse Transformers

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-05T13:58:40.774135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 69d77429-de0f-42ab-b58e-a0e96eb60c25 · inbound

Train, Retrieve, or Both? A Four-Arm Head-to-Head for Correct Statutory Citation on the Ontario Residential Tenancies Act cites this paper.

Train, Retrieve, or Both? A Four-Arm Head-to-Head for Correct Statutory Citation on the Ontario Residential Tenancies Act Scaling Legal AI: Benchmarking Mamba and Transformers for Statutory Classification and Case Law Retrieval

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-07-04T03:49:30.529619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.