Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Simple linear attention language models balance the recall-throughput tradeoff
As of 31 July 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:2402.18668.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-07-31T06:34:12.847434+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-12T00:55:09.690245Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-09T12:46:14.690167Z
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 d322e368-5474-4876-a035-e147d8543858 · inbound
Gated Linear Attention Transformers with Hardware-Efficient Training cites this paper.
Gated Linear Attention Transformers with Hardware-Efficient Training Simple linear attention language models balance the recall-throughput tradeoff
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T01:15:14.073801Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 229d7acd-8e21-4db7-9ae0-134f33aace2c · inbound
Gated Delta Networks: Improving Mamba2 with Delta Rule cites this paper.
Gated Delta Networks: Improving Mamba2 with Delta Rule Simple linear attention language models balance the recall-throughput tradeoff
Reference 296
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T14:50:24.348891Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation d14e9c0c-8ab4-4dc7-ac0a-e50b5dcd0e45 · inbound
Test-Time Training Done Right cites this paper.
Test-Time Training Done Right Simple linear attention language models balance the recall-throughput tradeoff
Reference 24
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T11:25:45.293597Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 4e9e2812-963f-4be3-a515-ffa9ded23632 · inbound
MT-PCR: Hybrid Mamba-Transformer Network with Spatial Serialization for Point Cloud Registration cites this paper.
MT-PCR: Hybrid Mamba-Transformer Network with Spatial Serialization for Point Cloud Registration Simple linear attention language models balance the recall-throughput tradeoff
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T10:02:14.454889Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation e68edf5f-de20-434f-bd6c-dfeda10c4553 · inbound
MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention cites this paper.
MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention Simple linear attention language models balance the recall-throughput tradeoff
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T09:28:16.364285Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation feee02e8-4167-4086-b813-553c338deed0 · inbound
Lizard: An Efficient Linearization Framework for Large Language Models cites this paper.
Lizard: An Efficient Linearization Framework for Large Language Models Simple linear attention language models balance the recall-throughput tradeoff
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T04:42:04.615556Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 48b2b299-549a-4c96-8e38-05136132d47f · inbound
Short window attention enables long-term memorization cites this paper.
Short window attention enables long-term memorization Simple linear attention language models balance the recall-throughput tradeoff
Reference 1
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-18T12:11:21.745803Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation a71564b5-7730-448f-b903-5e6343212713 · inbound
Phase-Associative Memory: Sequence Modeling in Complex Hilbert Space cites this paper.
Phase-Associative Memory: Sequence Modeling in Complex Hilbert Space Simple linear attention language models balance the recall-throughput tradeoff
Reference 116
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T22:40:48.904194Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 912a0589-8ddd-4c44-b99e-ea30dad3d442 · inbound
On The Application of Linear Attention in Multimodal Transformers cites this paper.
On The Application of Linear Attention in Multimodal Transformers Simple linear attention language models balance the recall-throughput tradeoff
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T07:20:59.541195Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 0baefe1d-c18c-4e1c-89f7-2abefe9005af · inbound
The Impossibility Triangle of Long-Context Modeling cites this paper.
The Impossibility Triangle of Long-Context Modeling Simple linear attention language models balance the recall-throughput tradeoff
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T17:41:09.139325Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 30699a9e-8d9c-4ba3-b48f-2e5d93f251ca · inbound
Adaptive Memory Decay for Log-Linear Attention cites this paper.
Adaptive Memory Decay for Log-Linear Attention Simple linear attention language models balance the recall-throughput tradeoff
Reference 22
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T04:50:56.338699Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation b70d82d9-3a87-4cb7-acb2-f4473fd7138f · inbound
OSDN: Improving Delta Rule with Provable Online Preconditioning in Linear Attention cites this paper.
OSDN: Improving Delta Rule with Provable Online Preconditioning in Linear Attention Simple linear attention language models balance the recall-throughput tradeoff
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T19:09:23.283089Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation b3613d75-f5e0-4efa-b32c-f0e338c798d9 · inbound
Do Language Models Need Sleep? Offline Recurrence for Improved Online Inference cites this paper.
Do Language Models Need Sleep? Offline Recurrence for Improved Online Inference Simple linear attention language models balance the recall-throughput tradeoff
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T21:43:59.535830Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 94956389-e873-4ed5-b249-1be6d045782b · inbound
Blurry Window Attention cites this paper.
Blurry Window Attention Simple linear attention language models balance the recall-throughput tradeoff
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T20:46:13.982781Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 2cbf092b-14d8-41e9-b3f0-18b3a687240c · inbound
Morphing into Hybrid Attention Models cites this paper.
Morphing into Hybrid Attention Models Simple linear attention language models balance the recall-throughput tradeoff
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T08:44:27.957941Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 3ff2fbb9-3a8d-4431-9cef-52884ac35647 · inbound
A Hippocampus for Linear Attention: An Exact Memory for What the Recurrent State Forgets cites this paper.
A Hippocampus for Linear Attention: An Exact Memory for What the Recurrent State Forgets Simple linear attention language models balance the recall-throughput tradeoff
Reference 2
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-03T13:48:20.324424Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation d3041a8a-b871-45c9-ad07-36985315ceeb · inbound
ELiTeFormer: An Efficient Transformer for FPGAs cites this paper.
ELiTeFormer: An Efficient Transformer for FPGAs Simple linear attention language models balance the recall-throughput tradeoff
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-07-12T00:55:09.690245Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b26e3a14-0621-48cc-9cdf-6859d42ef993 · inbound
Sparse Delta Memory: Scaling the State of Linear RNNs through Sparsity cites this paper.
Sparse Delta Memory: Scaling the State of Linear RNNs through Sparsity Simple linear attention language models balance the recall-throughput tradeoff
Reference 80
- Resolution
- verified exact
- local_arxiv, observed 2026-07-09T12:46:14.691577Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.