Paper Citation Record · LEDGER

Comparison of different Unique hard attention transformer models by the formal languages they can recognize

As of 8 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2506.03370.

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

pith.paper-citation-record.v1
2506.03370 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:14:00.876685Z

measured 13 of 13 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

13 of 13 outbound references displayed

verified exact0
verified fuzzy12
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 58b8991f-a410-400c-85ed-014e7a996932 · outbound

This paper cites A theorem on probabilistic constant depth computations.

Comparison of different Unique hard attention transformer models by the formal languages they can recognize A theorem on probabilistic constant depth computations

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:14:04.863776Z

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.

Observation 60de64b8-851e-487c-a1c8-08b33f214424 · outbound

This paper cites Logical Languages Accepted by Transformer Encoders with Hard Attention, October 2023.

Comparison of different Unique hard attention transformer models by the formal languages they can recognize Logical Languages Accepted by Transformer Encoders with Hard Attention, October 2023

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:14:04.534788Z

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.

Observation 13dfd690-76f8-4a88-9041-bf2e70eeab69 · outbound

This paper cites Brzozowski and R.

Comparison of different Unique hard attention transformer models by the formal languages they can recognize Brzozowski and R

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:14:04.227723Z

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.

Observation c37835d1-3174-4302-be7e-21d0fe742371 · outbound

This paper cites First-order definable languages.

Comparison of different Unique hard attention transformer models by the formal languages they can recognize First-order definable languages

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:14:03.878847Z

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.

Observation a50dd50c-9719-4a66-a990-7452ebbfe6cb · outbound

This paper cites Computing approximate majority in ac0, 2023.

Comparison of different Unique hard attention transformer models by the formal languages they can recognize Computing approximate majority in ac0, 2023

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:14:03.593338Z

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.

Observation fb2f1390-0a2c-4dde-b1ed-a3bb98055e23 · outbound

This paper cites Theoretical limitations of self-attention in neural sequence models.Transactions of the Asso- ciation for Computational Linguistics, 8:156–171, 2020.

Comparison of different Unique hard attention transformer models by the formal languages they can recognize Theoretical limitations of self-attention in neural sequence models.Transactions of the Asso- ciation for Computational Linguistics, 8:156–171, 2020

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:14:03.235531Z

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.

Observation 11812967-d25a-4139-9133-6f67bd8f897c · outbound

This paper cites Formal Language Recognition by Hard Attention Transformers: Perspectives from Circuit Complexity, April 2022.

Comparison of different Unique hard attention transformer models by the formal languages they can recognize Formal Language Recognition by Hard Attention Transformers: Perspectives from Circuit Complexity, April 2022

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:14:02.913027Z

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.

Observation f177d7d5-e391-4aba-be5b-5fdd15822af2 · outbound

This paper cites Logical languages accepted by transformer encoders with hard attention, 2023.

Comparison of different Unique hard attention transformer models by the formal languages they can recognize Logical languages accepted by transformer encoders with hard attention, 2023

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:14:02.616828Z

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.

Observation ce674e52-3e62-4e90-92a8-a41d68f81abd · outbound

This paper cites Temporal logic with past is exponentially more succinct, concurrency column.Bull.

Comparison of different Unique hard attention transformer models by the formal languages they can recognize Temporal logic with past is exponentially more succinct, concurrency column.Bull

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:14:02.328152Z

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.

Observation 78432bbc-de10-4795-b600-d5db6d39f209 · outbound

This paper cites an unresolved cited work.

Comparison of different Unique hard attention transformer models by the formal languages they can recognize Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:14:02.047227Z

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.

Observation eb371ab5-1b1b-4c69-92fa-0f1ba2de0452 · outbound

This paper cites Thinking Like Transformers.

Comparison of different Unique hard attention transformer models by the formal languages they can recognize Thinking Like Transformers

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:14:01.794736Z

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.

Observation c3709c9b-9ec1-4e6d-9be2-8d5929f5e05b · outbound

This paper cites Masked Hard-Attention Transformers Recognize Exactly the Star-Free Languages, May 2024.

Comparison of different Unique hard attention transformer models by the formal languages they can recognize Masked Hard-Attention Transformers Recognize Exactly the Star-Free Languages, May 2024

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:14:01.490730Z

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.

Observation 07d8d2ea-89e9-4964-885e-ed0c1538f269 · outbound

This paper cites Self-attention networks can process bounded hierarchical languages.

Comparison of different Unique hard attention transformer models by the formal languages they can recognize Self-attention networks can process bounded hierarchical languages

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:14:01.154027Z

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.

Pith citing papers

No inbound Pith citation observations are available.