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Paper Citation Record · LEDGER

HGRN2: Gated Linear RNNs with State Expansion

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 30 inbound Pith citation observations for arXiv:2404.07904.

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

pith.paper-citation-record.v1
2404.07904 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 30 of 30 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:22:28.467675Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T17:28:44.977281Z

Reference resolution

0 of 0 outbound references displayed

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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 028141c2-506e-482e-9706-b95408296bc9 · inbound

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

Gated Linear Attention Transformers with Hardware-Efficient Training HGRN2: Gated Linear RNNs with State Expansion

Reference 75

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arxiv_id, observed 2026-05-15T01:15:14.178481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-15T01:15:13.991219Z digest=sha256:7a8957d1dcc0efb87c4d00aa9458d7f1e5c7a4df108fe48c77c53e9944d19d42

Observation 3180dd9b-e417-4b83-bb09-9c7aee3395a6 · 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 HGRN2: Gated Linear RNNs with State Expansion

Reference 84

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:16:25.924691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation cdfc1606-882b-4c46-9e3a-584d247c356c · inbound

State Space Models are Strong Text Rerankers cites this paper.

State Space Models are Strong Text Rerankers HGRN2: Gated Linear RNNs with State Expansion

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-11T12:22:28.467675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:22:28.467675Z digest=sha256:e68830cd745d8291415ffcc9e787f025bd22d56efb0eb8ef50ac20489df2286c

Observation bb9dc605-5b32-4362-95c2-dfc742b0af19 · inbound

Understanding and Mitigating Bottlenecks of State Space Models through the Lens of Recency and Over-smoothing cites this paper.

Understanding and Mitigating Bottlenecks of State Space Models through the Lens of Recency and Over-smoothing HGRN2: Gated Linear RNNs with State Expansion

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-10T22:52:33.568763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:52:33.568763Z digest=sha256:015add772e2c7e8326c079c1859685937ffbde115901bbe28c6dfa5b118d5c5f

Observation 1bd148f1-0b79-4d3e-b370-2b16168f3bca · inbound

An Uncertainty Principle for Linear Recurrent Neural Networks cites this paper.

An Uncertainty Principle for Linear Recurrent Neural Networks HGRN2: Gated Linear RNNs with State Expansion

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T22:10:15.909661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:10:15.909661Z digest=sha256:0fdafd45179fba32656333ac1a17677714802834d04839aea12cddd1fdbbbfaf

Observation 53e3cf3f-bd85-4455-9a3e-65a41694f548 · inbound

Neuromorphic Principles for Efficient Large Language Models on Intel Loihi 2 cites this paper.

Neuromorphic Principles for Efficient Large Language Models on Intel Loihi 2 HGRN2: Gated Linear RNNs with State Expansion

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-08T10:59:50.623523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T10:59:50.623523Z digest=sha256:5393106f1171f2e652954cf82cb5c2cb17555fb708a6468d2a24fa7b0027b655

Observation 573992a7-f2eb-43aa-b04e-c85c2dff66dd · inbound

Autoregressive Image Generation with Linear Complexity: A Spatial-Aware Decay Perspective cites this paper.

Autoregressive Image Generation with Linear Complexity: A Spatial-Aware Decay Perspective HGRN2: Gated Linear RNNs with State Expansion

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-06T20:53:49.949048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:53:49.949048Z digest=sha256:d0c75205a3f50fec6cc6b8fd0cf6ac44ea41353590c9de9a721cb68bbfb898fe

Observation cd664a8c-0092-49a1-b441-3ec3454ef6ee · inbound

A Survey on Latent Reasoning cites this paper.

A Survey on Latent Reasoning HGRN2: Gated Linear RNNs with State Expansion

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-06T19:14:29.778788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:14:29.778788Z digest=sha256:a5fe10779c924174401167209805cedc1f5b377218f299867e98f6299017be4f

Observation 6f9b6f7c-42b2-4d19-9f4f-fb6d6cc589ad · inbound

Elucidating the Design Space of Decay in Linear Attention cites this paper.

Elucidating the Design Space of Decay in Linear Attention HGRN2: Gated Linear RNNs with State Expansion

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-05T05:29:21.596988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T05:29:21.596988Z digest=sha256:f547d9561e901c106e5579200cb305a00a539e803e6c68ebc3afda769753645a

Observation 4b894af1-4bf3-4a35-8a49-af66b2722404 · inbound

Nirvana: A Specialized Generalist Model With Task-Aware Memory Mechanism cites this paper.

Nirvana: A Specialized Generalist Model With Task-Aware Memory Mechanism HGRN2: Gated Linear RNNs with State Expansion

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-18T03:05:48.046309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 2fc4299c-e2db-4779-aba3-9f49db45f35f · inbound

Kimi Linear: An Expressive, Efficient Attention Architecture cites this paper.

Kimi Linear: An Expressive, Efficient Attention Architecture HGRN2: Gated Linear RNNs with State Expansion

Reference 78

Resolution
verified exact
arxiv_id, observed 2026-05-13T23:49:10.756376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-13T23:49:10.555255Z digest=sha256:9cb5f5da253f53aed27b03d7efa64a6f29abdd28efebf1cd7f7914a622b99701

Observation 4fbf30cf-0485-4cbc-ab7b-b2ff3e879222 · inbound

Selective Rotary Position Embedding cites this paper.

Selective Rotary Position Embedding HGRN2: Gated Linear RNNs with State Expansion

Reference 51

Resolution
verified exact
arxiv_id, observed 2026-05-17T20:40:14.876027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-17T20:36:49.650895Z digest=sha256:84fd91457153d865cf738de65dbeb1c693e429e8be4f88e04af8640748146330

Observation 57230f3d-9378-40cb-8c2f-cebced81accd · inbound

Selective Rotary Position Embedding cites this paper.

Selective Rotary Position Embedding HGRN2: Gated Linear RNNs with State Expansion

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-03T21:03:22.534290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T21:03:22.534290Z digest=sha256:bc513ca236738f9717860497f9d8ba898313f01d4e08e1c9de77f5aac0374c88

Observation 2462ea1a-cdd9-4d42-aa05-ab26cce44ba9 · inbound

Test-Time Training with KV Binding Is Secretly Linear Attention cites this paper.

Test-Time Training with KV Binding Is Secretly Linear Attention HGRN2: Gated Linear RNNs with State Expansion

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-15T19:41:32.655604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 256821c7-39ac-4d26-bc67-d7e1a707ad25 · inbound

Attention Residuals cites this paper.

Attention Residuals HGRN2: Gated Linear RNNs with State Expansion

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-05-21T06:39:04.421192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-21T06:39:04.312270Z digest=sha256:8a77935e0d1d7abe29fa8081e8e43321d3038f1d724b150c254199e106bed4eb

Observation f09d6923-58ed-4883-a640-16d130ffb17e · inbound

FG$^2$-GDN: Enhancing Long-Context Gated Delta Networks with Doubly Fine-Grained Control cites this paper.

FG$^2$-GDN: Enhancing Long-Context Gated Delta Networks with Doubly Fine-Grained Control HGRN2: Gated Linear RNNs with State Expansion

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-11T13:01:23.745730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 09aa5059-09a1-4359-aefd-d3ac460fc2ea · inbound

The Impossibility Triangle of Long-Context Modeling cites this paper.

The Impossibility Triangle of Long-Context Modeling HGRN2: Gated Linear RNNs with State Expansion

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-11T17:41:08.965747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 3d723a27-c177-4a9d-bf34-390fced108ca · inbound

Cubit: Token Mixer with Kernel Ridge Regression cites this paper.

Cubit: Token Mixer with Kernel Ridge Regression HGRN2: Gated Linear RNNs with State Expansion

Reference 61

Resolution
verified exact
arxiv_id, observed 2026-05-11T19:06:10.811375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation c8242dce-7d6d-41ea-ac26-ad571e9917a8 · inbound

Cubit: Token Mixer with Kernel Ridge Regression cites this paper.

Cubit: Token Mixer with Kernel Ridge Regression HGRN2: Gated Linear RNNs with State Expansion

Reference 61

Resolution
verified exact
arxiv_id, observed 2026-05-20T22:39:11.022749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 286fdac0-1d10-48d5-83b3-abbc37c78f17 · inbound

Elastic Attention Cores for Scalable Vision Transformers cites this paper.

Elastic Attention Cores for Scalable Vision Transformers HGRN2: Gated Linear RNNs with State Expansion

Reference 80

Resolution
verified exact
arxiv_id, observed 2026-05-13T06:07:22.515060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 11cc2d6a-49c9-4f2f-95bf-a83671a01053 · inbound

SpikeProphecy: A Large-Scale Benchmark for Autoregressive Neural Population Forecasting cites this paper.

SpikeProphecy: A Large-Scale Benchmark for Autoregressive Neural Population Forecasting HGRN2: Gated Linear RNNs with State Expansion

Reference 5

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verified exact
arxiv_id, observed 2026-05-14T02:18:37.510692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-14T02:17:34.631149Z digest=sha256:610f3e074c116c586f9be36ea0cd33282f7fad70551c89577f2be4c9de7edba8

Observation 2a073cd0-b19c-4d8e-9003-5973ba72f6e0 · inbound

LT2: Linear-Time Looped Transformers cites this paper.

LT2: Linear-Time Looped Transformers HGRN2: Gated Linear RNNs with State Expansion

Reference 50

Resolution
verified exact
arxiv_id, observed 2026-05-21T06:13:59.615527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 7fada328-71dc-4991-8818-72c4914f5af7 · inbound

LT2: Linear-Time Looped Transformers cites this paper.

LT2: Linear-Time Looped Transformers HGRN2: Gated Linear RNNs with State Expansion

Reference 50

Resolution
verified exact
arxiv_id, observed 2026-06-30T17:54:57.816696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-06-30T17:52:25.401671Z digest=sha256:1ff5f9e44d717c229392d763ae40691c39597951dfaff331ac58682215003b9b

Observation 2af5326e-6c1c-4c7a-8052-81474fca269d · inbound

Gated DeltaNet-2: Decoupling Erase and Write in Linear Attention cites this paper.

Gated DeltaNet-2: Decoupling Erase and Write in Linear Attention HGRN2: Gated Linear RNNs with State Expansion

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-05-22T04:54:36.620527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 7bf3a3f5-a8fe-4aaa-8b4e-07f072b5ffef · inbound

Universal Time Series Generation with Neural Controlled Differential Equations cites this paper.

Universal Time Series Generation with Neural Controlled Differential Equations HGRN2: Gated Linear RNNs with State Expansion

Reference 54

Resolution
verified exact
arxiv_id, observed 2026-06-29T14:13:30.017761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-06-29T14:10:38.078991Z digest=sha256:7875b0fe6f7dabcd7f45625e24ef37497c2d0f7357c4aef7400ef146f2b40363

Observation 06e63161-e187-4f3d-b004-5d4da99d1b39 · inbound

Memory by Design: Probabilistic Sequence Layers cites this paper.

Memory by Design: Probabilistic Sequence Layers HGRN2: Gated Linear RNNs with State Expansion

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-07-01T20:26:12.859084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-06-28T21:07:31.407554Z digest=sha256:bbfe32555696ac749701e6731fd77e2205daa2587eacb81cf01ffc0169b05806

Observation c413e580-7b36-4bea-888e-fe0e4cf2d629 · inbound

Dynamic Short Convolutions Improve Transformers cites this paper.

Dynamic Short Convolutions Improve Transformers HGRN2: Gated Linear RNNs with State Expansion

Reference 174

Resolution
verified exact
arxiv_id, observed 2026-07-02T02:36:27.001391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-06-28T10:48:50.103004Z digest=sha256:920b24b6cde5f8c947450b2c92d13bb59d3451d5ad6b46b12ae65ebdbb309039

Observation a1d64929-c85f-4d00-a050-bcb460179fa0 · inbound

Architecture-Aware Reinforcement Learning Makes Sliding-Window Attention Competitive in Math Reasoning cites this paper.

Architecture-Aware Reinforcement Learning Makes Sliding-Window Attention Competitive in Math Reasoning HGRN2: Gated Linear RNNs with State Expansion

Reference 76

Resolution
verified exact
arxiv_id, observed 2026-07-03T09:47:59.839072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-06-27T10:18:54.163862Z digest=sha256:f81badbf29bd5ae32d645604666b32f34a7fdf1724846722766c15780a309b8f

Observation 4f22a659-6728-4a2c-a2ea-e049194f67f6 · 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 HGRN2: Gated Linear RNNs with State Expansion

Reference 185

Resolution
verified exact
arxiv_id, observed 2026-07-03T17:28:44.978700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-06-27T04:02:53.110012Z digest=sha256:eafc9dcde98b517b559e5faa4fe2bcab4ef9c947d896d28e50553857fba7adc6

Observation 7d24fd88-1556-4edf-a88b-f2fd67fe5c67 · inbound

Morphing into Hybrid Attention Models cites this paper.

Morphing into Hybrid Attention Models HGRN2: Gated Linear RNNs with State Expansion

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-06-30T08:44:28.077887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-06-30T05:56:51.447893Z digest=sha256:759b7974d612215304bfb399186a6a915f4e0a3dad6b04a12bcf650381970562