Paper Citation Record · LEDGER

GateLoop: Fully Data-Controlled Linear Recurrence for Sequence Modeling

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2311.01927.

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

pith.paper-citation-record.v1
2311.01927 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T19:28:29.729282Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T16:09:56.603945Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a9d53376-924b-4d11-bbc1-a0f3f0255faf · inbound

Gated Linear Attention Transformers with Hardware-Efficient Training cites this paper.

Gated Linear Attention Transformers with Hardware-Efficient Training GateLoop: Fully Data-Controlled Linear Recurrence for Sequence Modeling

Reference 43

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T01:15:14.126508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2e74e5b8-18d7-4c59-85a4-db39883f2d70 · inbound

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models cites this paper.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models GateLoop: Fully Data-Controlled Linear Recurrence for Sequence Modeling

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:58:17.539189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ec5bfb2f-a766-47ea-9df8-8b16718ec6a7 · inbound

Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality cites this paper.

Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality GateLoop: Fully Data-Controlled Linear Recurrence for Sequence Modeling

Reference 53

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T12:16:25.801781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 161f766f-59aa-42d7-83b3-44d076c0b5f1 · inbound

MetaLA: Unified Optimal Linear Approximation to Softmax Attention Map cites this paper.

MetaLA: Unified Optimal Linear Approximation to Softmax Attention Map GateLoop: Fully Data-Controlled Linear Recurrence for Sequence Modeling

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-12T19:28:29.729282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11150208-117f-4ebd-be29-2eb91f3af28d · inbound

Selective Attention: Enhancing Transformer through Principled Context Control cites this paper.

Selective Attention: Enhancing Transformer through Principled Context Control GateLoop: Fully Data-Controlled Linear Recurrence for Sequence Modeling

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-12T17:12:32.714550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5f631c2-e4ad-4f5a-af33-f01f7ffea9a8 · inbound

Test-time regression: a unifying framework for designing sequence models with associative memory cites this paper.

Test-time regression: a unifying framework for designing sequence models with associative memory GateLoop: Fully Data-Controlled Linear Recurrence for Sequence Modeling

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-10T17:22:07.162271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed85b004-f9b5-44d2-9a19-9834dcfa2bba · inbound

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions cites this paper.

Let SSMs be ConvNets: State-space Modeling with Optimal Tensor Contractions GateLoop: Fully Data-Controlled Linear Recurrence for Sequence Modeling

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-10T16:26:51.236548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation daf0b013-ef49-4106-8281-d1cfdcf8b957 · inbound

Latent Mamba Operator for Partial Differential Equations cites this paper.

Latent Mamba Operator for Partial Differential Equations GateLoop: Fully Data-Controlled Linear Recurrence for Sequence Modeling

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:44.040741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5390f1c1-2d5c-41c8-826b-44725ebc0b97 · inbound

Phase-Associative Memory: Sequence Modeling in Complex Hilbert Space cites this paper.

Phase-Associative Memory: Sequence Modeling in Complex Hilbert Space GateLoop: Fully Data-Controlled Linear Recurrence for Sequence Modeling

Reference 98

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:40:48.709906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation de4870d6-2310-4d59-a2bd-ca5ec079978b · inbound

Learning to Adapt: In-Context Learning Beyond Stationarity cites this paper.

Learning to Adapt: In-Context Learning Beyond Stationarity GateLoop: Fully Data-Controlled Linear Recurrence for Sequence Modeling

Reference 25

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T08:45:59.388277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ee756dc8-5df0-4f4b-8942-da09043d9b51 · inbound

Kaczmarz Linear Attention cites this paper.

Kaczmarz Linear Attention GateLoop: Fully Data-Controlled Linear Recurrence for Sequence Modeling

Reference 18

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T08:06:37.006714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 46716332-0f16-412e-8099-76bdaec1c902 · inbound

Towards Understanding Self-Pretraining for Sequence Classification cites this paper.

Towards Understanding Self-Pretraining for Sequence Classification GateLoop: Fully Data-Controlled Linear Recurrence for Sequence Modeling

Reference 90

Resolution: verified exact; arxiv_id, observed 2026-05-21T05:33:58.924791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d64c0408-4e4b-48fd-b24e-08b6947db498 · inbound

Dynamic Short Convolutions Improve Transformers cites this paper.

Dynamic Short Convolutions Improve Transformers GateLoop: Fully Data-Controlled Linear Recurrence for Sequence Modeling

Reference 71

Resolution: verified exact; arxiv_id, observed 2026-07-02T02:36:27.034605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 985a420d-a17f-4011-bf7e-bd3f43acfa15 · inbound

Kairos: A Regret-Aware Native World-Action Model Stack for Physical AI cites this paper.

Kairos: A Regret-Aware Native World-Action Model Stack for Physical AI GateLoop: Fully Data-Controlled Linear Recurrence for Sequence Modeling

Reference 186

Resolution: verified exact; arxiv_id, observed 2026-07-03T17:28:44.887107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5241b57a-0434-4e4c-b86c-41795579cfae · inbound

Why Do Accumulated Transformations Extrapolate? cites this paper.

Why Do Accumulated Transformations Extrapolate? GateLoop: Fully Data-Controlled Linear Recurrence for Sequence Modeling

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-07-04T16:09:56.605708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.