Paper Citation Record · LEDGER

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

As of 18 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 100 inbound Pith citation observations for arXiv:2402.19427.

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

pith.paper-citation-record.v1
2402.19427 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-15T06:58:17.370396Z

measured 140 of 140 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 100 of 109 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:19:30.286857Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

40 of 40 outbound references displayed

verified exact34
verified fuzzy4
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

8
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 87cf6716-212c-4ad6-9893-b3cc7fb964fc · outbound

This paper cites GPT-4 Technical Report.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models GPT-4 Technical Report

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-05-15T06:58:17.404105Z

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 09c0fc6e-96a3-46af-bd4f-7379ef746ff6 · outbound

This paper cites Neural Machine Translation by Jointly Learning to Align and Translate.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Neural Machine Translation by Jointly Learning to Align and Translate

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-05-15T06:58:17.411532Z

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 3159a262-5e7d-4778-98d0-e2f5f701be8f · outbound

This paper cites Longformer: The Long-Document Transformer.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Longformer: The Long-Document Transformer

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-05-15T06:58:17.418193Z

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 1eec6377-7683-443d-900a-c9ea21c084a4 · outbound

This paper cites Quasi-Recurrent Neural Networks.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Quasi-Recurrent Neural Networks

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-05-15T06:58:17.423878Z

Source-reported events for the cited work

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Observation 2318a795-c3f2-4416-a960-ba6f7c47c756 · outbound

This paper cites T.Brown,B.Mann,N.Ryder,M.Subbiah,J.D.Kaplan,P.Dhariwal,A.Neelakantan,P.Shyam,G.Sastry, A.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models T.Brown,B.Mann,N.Ryder,M.Subbiah,J.D.Kaplan,P.Dhariwal,A.Neelakantan,P.Shyam,G.Sastry, A

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T06:58:17.614165Z

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 c33bcbbb-ef9b-4a3e-9f87-9d6a57a05915 · outbound

This paper cites Generating Long Sequences with Sparse Transformers.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Generating Long Sequences with Sparse Transformers

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-05-15T06:58:17.469338Z

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 55ee1edb-eb88-4c0f-8c5f-98566dd9df0f · outbound

This paper cites Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-05-15T06:58:17.474817Z

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 5b5c40d6-e234-4fdd-b727-9b7e275ac8ae · outbound

This paper cites Hungry Hungry Hippos: Towards Language Modeling with State Space Models.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Hungry Hungry Hippos: Towards Language Modeling with State Space Models

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:58:17.482210Z

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 6e4486d7-ce5c-4c22-a8db-ec209bdd790c · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Gemini: A Family of Highly Capable Multimodal Models

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-05-15T06:58:17.488268Z

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 e19687ef-b041-4cc8-a9c0-99459888b257 · outbound

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

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-05-15T06:58:17.494676Z

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 4ff28c73-b19e-4a42-946a-cbcbaebd3c2c · outbound

This paper cites Efficiently Modeling Long Sequences with Structured State Spaces.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Efficiently Modeling Long Sequences with Structured State Spaces

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-05-15T06:58:17.501302Z

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 0d3ed0ee-309d-4b95-afe4-dfd78e21c628 · outbound

This paper cites Gaussian Error Linear Units (GELUs).

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Gaussian Error Linear Units (GELUs)

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-05-15T06:58:17.507685Z

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 88e56c38-da17-4c57-9681-d19afd23902e · outbound

This paper cites Training Compute-Optimal Large Language Models.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Training Compute-Optimal Large Language Models

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-05-15T06:58:17.513427Z

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 4785e0e2-ffce-4e15-87fe-1fa1c43050d1 · outbound

This paper cites Repeat After Me: Transformers are Better than State Space Models at Copying.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Repeat After Me: Transformers are Better than State Space Models at Copying

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:58:17.519265Z

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 df4db80d-37ac-4ded-a8b4-632fe1c177d5 · outbound

This paper cites Mistral 7B.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Mistral 7B

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-05-15T06:58:17.525125Z

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 4d88dc55-0d64-41e8-97b3-4810ca6b7ef9 · outbound

This paper cites an unresolved cited work.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-05-15T06:58:17.617708Z

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 79320dd5-00a0-45de-9a30-1e04cd95b9ee · outbound

This paper cites Scaling Laws for Neural Language Models.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Scaling Laws for Neural Language Models

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-05-15T06:58:17.532642Z

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 · outbound

This paper cites GateLoop: Fully Data-Controlled Linear Recurrence for Sequence Modeling.

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 d642502c-c943-4d42-a12d-22b4c622f805 · outbound

This paper cites Advances in Neural Information Processing Systems,36.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Advances in Neural Information Processing Systems,36

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T06:58:17.629689Z

Source-reported events for the cited work

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Observation 92df91aa-32dc-4d4b-ab6a-87b2f27590c3 · outbound

This paper cites Decoupled Weight Decay Regularization.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Decoupled Weight Decay Regularization

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-05-15T06:58:17.544914Z

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 5faca210-37cd-46fe-b80f-67a2fe77813a · outbound

This paper cites Parallelizing Linear Recurrent Neural Nets Over Sequence Length.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Parallelizing Linear Recurrent Neural Nets Over Sequence Length

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-05-15T06:58:17.550241Z

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 6a8aa7f5-c97c-4e5a-bd25-04adefc0fc7c · outbound

This paper cites Long Range Language Modeling via Gated State Spaces.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Long Range Language Modeling via Gated State Spaces

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:58:17.555498Z

Source-reported events for the cited work

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Observation f6b4b095-2935-4e4d-bbdd-fd1421e6287c · outbound

This paper cites Universality of Linear Recurrences Followed by Non-linear Projections: Finite-Width Guarantees and Benefits of Complex Eigenvalues.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Universality of Linear Recurrences Followed by Non-linear Projections: Finite-Width Guarantees and Benefits of Complex Eigenvalues

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:58:17.560747Z

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 18c879ba-ebab-48c9-b250-077258870c42 · outbound

This paper cites Hyena Hierarchy: Towards Larger Convolutional Language Models.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Hyena Hierarchy: Towards Larger Convolutional Language Models

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:58:17.566956Z

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 992899c5-c7d4-46d2-8001-8d4a8435d8cd · outbound

This paper cites Scaling Language Models: Methods, Analysis & Insights from Training Gopher.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Scaling Language Models: Methods, Analysis & Insights from Training Gopher

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-05-15T06:58:17.573112Z

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 8850c0a0-df23-4695-b680-4f56978a3535 · outbound

This paper cites Fast Transformer Decoding: One Write-Head is All You Need.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Fast Transformer Decoding: One Write-Head is All You Need

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-05-15T06:58:17.578807Z

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 790bdada-5db6-472b-a1e9-83e7d0303380 · outbound

This paper cites GLU Variants Improve Transformer.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models GLU Variants Improve Transformer

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-05-15T06:58:17.583949Z

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 3ff9f499-89a9-46ad-9ed4-a3bdf03cfa41 · outbound

This paper cites Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-05-15T06:58:17.592017Z

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 73b1b397-82a6-4ed8-9f81-2f94adb8ff41 · outbound

This paper cites Simplified State Space Layers for Sequence Modeling.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Simplified State Space Layers for Sequence Modeling

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-16T08:16:11.899530Z

Source-reported events for the cited work

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Observation 275ae357-f483-4b42-a1b2-b4e2a2ec6245 · outbound

This paper cites RoFormer: Enhanced Transformer with Rotary Position Embedding.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models RoFormer: Enhanced Transformer with Rotary Position Embedding

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-05-15T06:58:17.603924Z

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Observation f3a76fb5-52a8-4a4c-9ab1-75af503ea322 · outbound

This paper cites Retentive Network: A Successor to Transformer for Large Language Models.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Retentive Network: A Successor to Transformer for Large Language Models

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-05-15T06:58:17.609791Z

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 9c1fdd02-67de-4fbd-b50f-4c9d2e9dc6a2 · outbound

This paper cites Long Range Arena: A Benchmark for Efficient Transformers.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Long Range Arena: A Benchmark for Efficient Transformers

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:58:17.429964Z

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 baa54c77-d192-4123-9937-305d4535e876 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models LLaMA: Open and Efficient Foundation Language Models

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-05-15T06:58:17.435569Z

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 eedd0109-dc5b-4176-964b-d1704c146855 · outbound

This paper cites MambaByte: Token-free Selective State Space Model.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models MambaByte: Token-free Selective State Space Model

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:58:17.441699Z

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 61b73720-64f8-4586-9849-e616c6cf35f9 · outbound

This paper cites Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-05-15T06:58:17.450878Z

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

Observation 9073705e-3dfd-4def-a342-4df21a38486d · outbound

This paper cites An Attention Free Transformer.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models An Attention Free Transformer

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:58:17.456663Z

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 2c6f7f69-0934-4197-bfbc-f9f3fd7320ec · outbound

This paper cites Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

Reference 37

Resolution: verified exact; local_arxiv, observed 2026-05-15T06:58:17.463618Z

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 826ca3f4-8586-499a-ab66-85fae5056b78 · outbound

This paper cites (13) We mark all complex variables with˜·for clarity.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models (13) We mark all complex variables with˜·for clarity

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T06:58:17.634022Z

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 69dcc9dd-59ff-4712-a0e5-dec63b133fad · outbound

This paper cites an unresolved cited work.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models Unresolved cited work

Reference 39

Resolution: unresolved; raw_fallback, observed 2026-05-15T06:58:17.621278Z

Source-reported events for the cited work

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Observation 9cf9927a-fe44-4c45-9151-5c9b99f03a47 · outbound

This paper cites On the left, we compare the performance of different models trained with sequence length 2048, evaluated with a sequence length of up to 32,768.

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models On the left, we compare the performance of different models trained with sequence length 2048, evaluated with a sequence length of up to 32,768

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-15T06:58:17.625874Z

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.

Pith citing papers

Observation 06955ea7-2766-403c-925b-c1127bbe829c · 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 Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:58:17.635264Z

Source-reported events for the cited work

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Observation 2ea19612-848c-4781-bfc9-b911c4afd93d · inbound

An Empirical Study of Mamba-based Language Models cites this paper.

An Empirical Study of Mamba-based Language Models Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-05-18T10:31:03.952121Z

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 c3d1962c-1f0b-4826-be5d-5803d408ee51 · inbound

Learning to (Learn at Test Time): RNNs with Expressive Hidden States cites this paper.

Learning to (Learn at Test Time): RNNs with Expressive Hidden States Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:58:17.635264Z

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

Observation 33723dc7-91db-4d02-a714-deb19bd93a21 · inbound

LightTransfer: Your Long-Context LLM is Secretly a Hybrid Model with Effortless Adaptation cites this paper.

LightTransfer: Your Long-Context LLM is Secretly a Hybrid Model with Effortless Adaptation Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 10

Resolution: metadata mismatch; local_arxiv, observed 2026-05-23T18:33:19.409017Z

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 00c89e75-9697-4269-b1d7-89f40bde8b1c · inbound

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

MetaLA: Unified Optimal Linear Approximation to Softmax Attention Map Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T19:28:28.652035Z

Source-reported events for the cited work

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Observation 4ccf5561-4705-4e92-ba3c-7ceb6021ba38 · inbound

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

Selective Attention: Enhancing Transformer through Principled Context Control Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T17:12:32.680612Z

Source-reported events for the cited work

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Observation 221fdb52-126f-4b54-bf02-399f2e468f51 · inbound

Hymba: A Hybrid-head Architecture for Small Language Models cites this paper.

Hymba: A Hybrid-head Architecture for Small Language Models Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-12T16:20:32.762403Z

Source-reported events for the cited work

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Observation 57bfdbea-7147-42fb-af31-eec34fd06814 · inbound

CLOVER: Cross-Layer Orthogonal Vectors Pruning and Fine-Tuning cites this paper.

CLOVER: Cross-Layer Orthogonal Vectors Pruning and Fine-Tuning Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 2018

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Observation c080b9ca-69ca-40fd-978a-c69ae7276dd0 · inbound

Attamba: Attending To Multi-Token States cites this paper.

Attamba: Attending To Multi-Token States Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 6

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Marconi: Prefix Caching for the Era of Hybrid LLMs cites this paper.

Marconi: Prefix Caching for the Era of Hybrid LLMs Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 2022

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MAL: Cluster-Masked and Multi-Task Pretraining for Enhanced xLSTM Vision Performance cites this paper.

MAL: Cluster-Masked and Multi-Task Pretraining for Enhanced xLSTM Vision Performance Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 12

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Expansion Span: Combining Fading Memory and Retrieval in Hybrid State Space Models cites this paper.

Expansion Span: Combining Fading Memory and Retrieval in Hybrid State Space Models Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 9

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Observation 68e731b5-6662-4f69-862a-7e80fd990183 · inbound

On the Expressiveness and Length Generalization of Selective State-Space Models on Regular Languages cites this paper.

On the Expressiveness and Length Generalization of Selective State-Space Models on Regular Languages Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 9

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Observation ff742bf8-2803-48b4-990b-dd784d4ac900 · 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 Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 12

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Observation 4ad863bf-577d-4590-9214-3901ded4aafd · inbound

Titans: Learning to Memorize at Test Time cites this paper.

Titans: Learning to Memorize at Test Time Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 29

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Source-reported events for the cited work

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Observation 44ea67d5-8c86-4734-b520-6a1dbc847437 · inbound

MSWA: Refining Local Attention with Multi-ScaleWindow Attention cites this paper.

MSWA: Refining Local Attention with Multi-ScaleWindow Attention Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 18

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Source-reported events for the cited work

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Observation 7ba4b453-34a9-4e90-a3e4-bb2cb35c86f5 · 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 Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 20

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Observation 64bd7a44-1de4-491a-963a-53bee77dd574 · inbound

GRAMA: Adaptive Graph Autoregressive Moving Average Models cites this paper.

GRAMA: Adaptive Graph Autoregressive Moving Average Models Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 25

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Observation e9a88c47-c086-40f5-8f71-0df4b92ab72e · inbound

Explore Activation Sparsity in Recurrent LLMs for Energy-Efficient Neuromorphic Computing cites this paper.

Explore Activation Sparsity in Recurrent LLMs for Energy-Efficient Neuromorphic Computing Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 056e3391-19a9-482c-8f81-e5c0ee415e9c · inbound

On the Expressivity of Selective State-Space Layers: A Multivariate Polynomial Approach cites this paper.

On the Expressivity of Selective State-Space Layers: A Multivariate Polynomial Approach Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b16394b4-5d9a-4a44-8eae-af6350b2a513 · inbound

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

An Uncertainty Principle for Linear Recurrent Neural Networks Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 2022

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Observation be4a3871-60c1-495e-ab58-550edd005235 · inbound

Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention cites this paper.

Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 58

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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 0320d96b-4f2a-41e7-99e8-7e1a7cace126 · inbound

It's All Connected: A Journey Through Test-Time Memorization, Attentional Bias, Retention, and Online Optimization cites this paper.

It's All Connected: A Journey Through Test-Time Memorization, Attentional Bias, Retention, and Online Optimization Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T12:19:30.286857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e208c05f-fcd9-4ad1-babd-562f36e5412e · inbound

ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools cites this paper.

ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-16T11:34:26.698505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2dfb2a3-992d-46be-9a70-efcac9a03df4 · inbound

LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities cites this paper.

LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0fa4d082-08dd-4cc4-90f1-f21da8c1df1d · inbound

Quantifying Memory Utilization with Effective State-Size cites this paper.

Quantifying Memory Utilization with Effective State-Size Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69fb5a92-dc91-4efb-abf8-271cf9a58e50 · inbound

Vision Mamba in Remote Sensing: A Comprehensive Survey of Techniques, Applications and Outlook cites this paper.

Vision Mamba in Remote Sensing: A Comprehensive Survey of Techniques, Applications and Outlook Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 50

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation def813ee-7313-44f2-919a-5f6881eec9ed · inbound

Reasoning Capabilities and Invariability of Large Language Models cites this paper.

Reasoning Capabilities and Invariability of Large Language Models Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 34

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ced32ed0-de43-45dd-84c4-b0d6b4dff9f9 · inbound

Message-Passing State-Space Models: Improving Graph Learning with Modern Sequence Modeling cites this paper.

Message-Passing State-Space Models: Improving Graph Learning with Modern Sequence Modeling Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T14:32:36.596300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e69752c-4362-44d3-abba-04e2c13ff613 · inbound

Revisiting Glorot Initialization for Long-Range Linear Recurrences cites this paper.

Revisiting Glorot Initialization for Long-Range Linear Recurrences Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-07T14:14:08.747322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e84e033-a2a6-4b5f-af98-82f51edd9fb1 · inbound

Sparsified State-Space Models are Efficient Highway Networks cites this paper.

Sparsified State-Space Models are Efficient Highway Networks Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-07T13:54:45.020020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62752f89-cdd0-4fdc-a32d-e0684ef8d378 · inbound

Geometric Hyena Networks for Large-scale Equivariant Learning cites this paper.

Geometric Hyena Networks for Large-scale Equivariant Learning Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51c5621c-26de-4fc5-a3fb-9b8fc8667510 · inbound

MesaNet: Sequence Modeling by Locally Optimal Test-Time Training cites this paper.

MesaNet: Sequence Modeling by Locally Optimal Test-Time Training Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:12.746450Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55da58e0-17ae-4336-a8a0-252aad8ba740 · inbound

A Survey of Retentive Network cites this paper.

A Survey of Retentive Network Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 16

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e10fe4ab-9031-49e5-a69c-d6f1a50e3800 · inbound

Routing Mamba: Scaling State Space Models with Mixture-of-Experts Projection cites this paper.

Routing Mamba: Scaling State Space Models with Mixture-of-Experts Projection Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T23:28:44.335630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebc456d3-14e0-4f9f-ab24-06bafc44b2d6 · inbound

MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent cites this paper.

MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-05-15T11:17:24.628777Z

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 c333a267-75e7-4be8-bc80-e3cfba4385c1 · inbound

MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent cites this paper.

MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-06T20:40:11.917229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 889cdfca-77ea-444e-be11-5f1d974dba96 · inbound

AuroraLong: Bringing RNNs Back to Efficient Open-Ended Video Understanding cites this paper.

AuroraLong: Bringing RNNs Back to Efficient Open-Ended Video Understanding Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T20:29:49.624319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3434b521-120a-42f8-ba19-6eb9e017bf1d · inbound

A Systematic Analysis of Hybrid Linear Attention cites this paper.

A Systematic Analysis of Hybrid Linear Attention Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 33

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad621e97-2937-4b58-bf06-027b3959d7c1 · inbound

Lizard: An Efficient Linearization Framework for Large Language Models cites this paper.

Lizard: An Efficient Linearization Framework for Large Language Models Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 6

Resolution: metadata mismatch; local_arxiv, observed 2026-05-19T04:42:04.534710Z

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 1391d620-ee6f-4a0c-9b19-b0c38e309ee1 · inbound

Falcon-H1: A Family of Hybrid-Head Language Models Redefining Efficiency and Performance cites this paper.

Falcon-H1: A Family of Hybrid-Head Language Models Redefining Efficiency and Performance Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T11:44:04.925289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3708a5fe-043a-4854-917d-3b1719bd4270 · inbound

SpikingBrain: Spiking Brain-inspired Large Models cites this paper.

SpikingBrain: Spiking Brain-inspired Large Models Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-05-18T18:51:45.775697Z

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 9f1ea1b3-5a5c-4b25-ba5a-f1778b03a762 · inbound

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

Elucidating the Design Space of Decay in Linear Attention Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T05:29:21.297289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48db92f2-b4c7-4b96-867b-744794c02828 · inbound

Short window attention enables long-term memorization cites this paper.

Short window attention enables long-term memorization Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-05-18T12:11:21.808263Z

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 82a3cfd6-46e4-4b09-877f-f83ccafb0747 · inbound

Hybrid Architectures for Language Models: Systematic Analysis and Design Insights cites this paper.

Hybrid Architectures for Language Models: Systematic Analysis and Design Insights Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-05-18T10:21:15.108907Z

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 60ec5ed0-64e6-4810-b69a-d0a5625e074e · inbound

DiffuMamba: High-Throughput Diffusion LMs with Mamba Backbone cites this paper.

DiffuMamba: High-Throughput Diffusion LMs with Mamba Backbone Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T21:20:34.467266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 863a79ef-9659-4fb0-b88e-684dc47799f3 · inbound

Selective Rotary Position Embedding cites this paper.

Selective Rotary Position Embedding Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-05-17T20:40:14.861957Z

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 499c3aa2-5ce8-4b8a-b40f-535f35f94d3b · inbound

Selective Rotary Position Embedding cites this paper.

Selective Rotary Position Embedding Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af9b1816-3b38-4915-8786-0b4661921526 · inbound

Gated KalmaNet: A Fading Memory Layer Through Test-Time Ridge Regression cites this paper.

Gated KalmaNet: A Fading Memory Layer Through Test-Time Ridge Regression Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-05-21T18:00:27.115409Z

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 6f226ae0-8f0e-4025-88d8-a9f70e0c8272 · inbound

Physics of Language Models: Part 4.1, Architecture Design and the Magic of Canon Layers cites this paper.

Physics of Language Models: Part 4.1, Architecture Design and the Magic of Canon Layers Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b83e026-48db-4285-9fa0-0126f68688f8 · inbound

Distill-then-Replace: Efficient Task-Specific Hybrid Attention Model Construction cites this paper.

Distill-then-Replace: Efficient Task-Specific Hybrid Attention Model Construction Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T10:12:43.396788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18a0e62c-33ee-474a-9528-d0cb10165e65 · inbound

When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models cites this paper.

When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 6

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T11:50:52.802578Z

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 38ac6792-76ff-4180-82a3-fead463c9dcf · inbound

RAT+: Train Dense, Infer Sparse -- Recurrence Augmented Attention for Dilated Inference cites this paper.

RAT+: Train Dense, Infer Sparse -- Recurrence Augmented Attention for Dilated Inference Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 8

Resolution: metadata mismatch; local_arxiv, observed 2026-05-15T21:00:17.897130Z

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 d4c25bb4-d24c-44a4-a2f9-991ef4125905 · inbound

RAT+: Train Dense, Infer Sparse -- Recurrence Augmented Attention for Dilated Inference cites this paper.

RAT+: Train Dense, Infer Sparse -- Recurrence Augmented Attention for Dilated Inference Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 8

Resolution: metadata mismatch; local_arxiv, observed 2026-05-21T12:50:09.519771Z

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 98aafb65-e4c0-4f2a-9a27-cbbbbc0b0d3d · inbound

RAT+: Train Dense, Infer Sparse -- Recurrence Augmented Attention for Dilated Inference cites this paper.

RAT+: Train Dense, Infer Sparse -- Recurrence Augmented Attention for Dilated Inference Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-02T22:05:42.987805Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation daa7580c-ff19-4d6f-8931-76acb0864547 · inbound

When Does Content-Based Routing Work? Representation Requirements for Selective Attention in Hybrid Sequence Models cites this paper.

When Does Content-Based Routing Work? Representation Requirements for Selective Attention in Hybrid Sequence Models Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:58:17.635264Z

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 50eab17c-36ae-4490-acd5-02b0dccfdb7d · inbound

When Perplexity Lies: Generation-Focused Distillation of Hybrid Sequence Models cites this paper.

When Perplexity Lies: Generation-Focused Distillation of Hybrid Sequence Models Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-02T17:21:21.451268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92a3e1eb-c599-41c1-a96a-74bd0879067a · inbound

LPC-SM: Local Predictive Coding and Sparse Memory for Long-Context Language Modeling cites this paper.

LPC-SM: Local Predictive Coding and Sparse Memory for Long-Context Language Modeling Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-05-15T11:25:31.080573Z

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 e0b7d0a9-90b9-4854-b824-0dab5b38ea57 · inbound

Mambalaya: Einsum-Based Fusion Optimizations on State-Space Models cites this paper.

Mambalaya: Einsum-Based Fusion Optimizations on State-Space Models Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:58:17.635264Z

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 df3bb33e-85ce-467e-a284-af7124e56847 · inbound

Mambalaya: Einsum-Based Fusion Optimizations on State-Space Models cites this paper.

Mambalaya: Einsum-Based Fusion Optimizations on State-Space Models Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T16:51:07.301614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cdce8f7-b0c3-485f-ade1-7cdee9c524c2 · inbound

CAWN: Continuous Acoustic Wave Networks for Autoregressive Language Modeling cites this paper.

CAWN: Continuous Acoustic Wave Networks for Autoregressive Language Modeling Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-13T10:31:11.574398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6400ba6b-3a57-4e36-9564-fd52ac10af70 · inbound

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

Phase-Associative Memory: Sequence Modeling in Complex Hilbert Space Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 101

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:58:17.635264Z

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 701eff04-23f3-44ac-b058-ca11003e9a80 · inbound

Optimal Decay Spectra for Linear Recurrences cites this paper.

Optimal Decay Spectra for Linear Recurrences Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:58:17.635264Z

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 a32ec29c-a010-4964-94b3-eecb39f70070 · inbound

TAPNext++: What's Next for Tracking Any Point (TAP)? cites this paper.

TAPNext++: What's Next for Tracking Any Point (TAP)? Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:58:17.635264Z

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 a45c8722-7873-4785-876a-8a40cd86a7dd · inbound

On the Expressive Power and Limitations of Multi-Layer SSMs cites this paper.

On the Expressive Power and Limitations of Multi-Layer SSMs Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:58:17.635264Z

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 56d86a29-2489-4db4-b253-f5d44635e2d1 · inbound

Scalable Memristive-Friendly Reservoir Computing for Time Series Classification cites this paper.

Scalable Memristive-Friendly Reservoir Computing for Time Series Classification Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:58:17.635264Z

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 75eff084-6ebd-43c0-856c-502724664f30 · inbound

HubRouter: A Pluggable Sub-Quadratic Routing Primitive for Hybrid Sequence Models cites this paper.

HubRouter: A Pluggable Sub-Quadratic Routing Primitive for Hybrid Sequence Models Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:58:17.635264Z

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 ddd9849a-3219-4fcf-b569-e3919cb12db7 · inbound

SpikingBrain2.0: Brain-Inspired Foundation Models for Efficient Long-Context and Cross-Platform Inference cites this paper.

SpikingBrain2.0: Brain-Inspired Foundation Models for Efficient Long-Context and Cross-Platform Inference Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:58:17.635264Z

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 089576dd-8998-4e0e-a175-7547cbf926bf · inbound

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

The Impossibility Triangle of Long-Context Modeling Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:58:17.635264Z

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 7340369a-81bb-4691-9c29-ce1f099bc359 · inbound

How Long Does Infinite Width Last? Signal Propagation in Long-Range Linear Recurrences cites this paper.

How Long Does Infinite Width Last? Signal Propagation in Long-Range Linear Recurrences Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:58:17.635264Z

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 4377f820-c8ca-440a-83e0-675a877b3276 · inbound

A Robust Foundation Model for Conservation Laws: Injecting Context into Flux Neural Operators via Recurrent Vision Transformers cites this paper.

A Robust Foundation Model for Conservation Laws: Injecting Context into Flux Neural Operators via Recurrent Vision Transformers Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T06:58:17.635264Z

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 64cc7df7-1c6f-4b56-b12a-afdc3eb9d202 · inbound

MDN: Parallelizing Stepwise Momentum for Delta Linear Attention cites this paper.

MDN: Parallelizing Stepwise Momentum for Delta Linear Attention Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T06:58:17.635264Z

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 96e8e322-c921-43a0-b314-a6df5715f1a1 · inbound

Priming: Hybrid State Space Models From Pre-trained Transformers cites this paper.

Priming: Hybrid State Space Models From Pre-trained Transformers Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:58:17.635264Z

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 790946f8-6032-4a68-b1ba-7269b092e9e3 · inbound

Kaczmarz Linear Attention cites this paper.

Kaczmarz Linear Attention Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:58:17.635264Z

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 401870ed-087a-44c5-b4b1-d6c4e4c9aeef · inbound

MemReread: Enhancing Agentic Long-Context Reasoning via Memory-Guided Rereading cites this paper.

MemReread: Enhancing Agentic Long-Context Reasoning via Memory-Guided Rereading Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:58:17.635264Z

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 9dfb6fda-8d60-4f2c-b257-bcb8a0fa20ed · inbound

A Single-Layer Model Can Do Language Modeling cites this paper.

A Single-Layer Model Can Do Language Modeling Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T06:58:17.635264Z

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 83d8a01a-56d0-4642-b16b-1c7036365860 · inbound

HexagonalWarriorMamba: Superior Threshold-Dependent Multi-label Classification of 12-Lead ECG Cardiac Abnormalities cites this paper.

HexagonalWarriorMamba: Superior Threshold-Dependent Multi-label Classification of 12-Lead ECG Cardiac Abnormalities Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-05-20T11:58:14.929076Z

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 e1fae2d7-c4ea-4e00-96f4-2c0b0b29b0dd · inbound

The Routing and Filtering Structure of Attention cites this paper.

The Routing and Filtering Structure of Attention Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-05-20T22:09:07.720892Z

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 0c87302f-66bf-4d22-bba4-ee4092b054db · inbound

Flash PD-SSM: Memory-Optimized Structured Sparse State-Space Models cites this paper.

Flash PD-SSM: Memory-Optimized Structured Sparse State-Space Models Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 12

Resolution: metadata mismatch; local_arxiv, observed 2026-05-20T11:53:15.168578Z

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 4aa09321-2184-4788-ac6f-37eaa4c3edd2 · inbound

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

Towards Understanding Self-Pretraining for Sequence Classification Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 101

Resolution: metadata mismatch; local_arxiv, observed 2026-05-21T05:33:58.868560Z

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 e4cfe493-1848-4837-9464-cef8867d4bcf · inbound

Interdomain Attention: Beyond Token-Level Key-Value Memory cites this paper.

Interdomain Attention: Beyond Token-Level Key-Value Memory Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 2

Resolution: metadata mismatch; local_arxiv, observed 2026-06-30T14:04:44.092256Z

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 9fab381a-a2bf-4a65-9094-474dbe26edb4 · 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 Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-06-29T21:43:59.493853Z

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 2efbb355-3685-403c-8cb5-003ce1c758cb · inbound

Latent Recurrent Transformer: Architecture Exploration, Training Strategies, and Scaling Behavior cites this paper.

Latent Recurrent Transformer: Architecture Exploration, Training Strategies, and Scaling Behavior Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-06-29T19:43:54.937865Z

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 e3f096b0-1cbd-4357-b8e1-626a9d28993d · inbound

Memory by Design: Probabilistic Sequence Layers cites this paper.

Memory by Design: Probabilistic Sequence Layers Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 8

Resolution: metadata mismatch; local_arxiv, observed 2026-07-01T20:26:12.920120Z

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 48ca4380-ab64-4ea9-aab1-9d50ceb66ddb · inbound

Trading Complexity for Expressivity Through Structured Generalized Linear Token Mixing cites this paper.

Trading Complexity for Expressivity Through Structured Generalized Linear Token Mixing Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 1

Resolution: metadata mismatch; local_arxiv, observed 2026-06-28T23:02:45.801805Z

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 88cd020b-e37e-4376-b097-65ad34fab426 · inbound

Forget Attention: Importance-Aware Attention Is All You Need cites this paper.

Forget Attention: Importance-Aware Attention Is All You Need Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 9

Resolution: metadata mismatch; local_arxiv, observed 2026-07-01T23:06:21.029340Z

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 02f27307-df19-4fa0-8a6a-6ce6cce7549b · inbound

LoopMoE: Unifying Iterative Computation with Mixture-of-Experts for Language Modeling cites this paper.

LoopMoE: Unifying Iterative Computation with Mixture-of-Experts for Language Modeling Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 42

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T06:36:44.182382Z

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 324b4bc8-0224-4646-9c55-f236ee2be205 · inbound

Titans-as-a-Layer: Test-Time Memory for Conversational Speech Emotion Recognition cites this paper.

Titans-as-a-Layer: Test-Time Memory for Conversational Speech Emotion Recognition Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 8

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T23:07:26.839436Z

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 b25d24ce-a02b-48a6-b3bd-039a3bc986c2 · inbound

Blurry Window Attention cites this paper.

Blurry Window Attention Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-07-01T20:46:14.017951Z

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 a25b4ef6-89f8-44d7-b979-031b11ffa75b · inbound

Free Parametrization of L_2-Bounded Structured State-Space Controllers for Nonlinear Control with Stability Guarantees cites this paper.

Free Parametrization of L_2-Bounded Structured State-Space Controllers for Nonlinear Control with Stability Guarantees Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-06-27T12:10:53.818017Z

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 e1a196cd-9290-4ccc-96b3-02e2ec849791 · inbound

PLUME: Probabilistic Latent Unified World Modeling and Parameter Estimation for Multi-Finger Manipulation cites this paper.

PLUME: Probabilistic Latent Unified World Modeling and Parameter Estimation for Multi-Finger Manipulation Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 47

Resolution: verified exact; local_arxiv, observed 2026-07-03T06:17:41.379799Z

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 63a05911-a45c-4fd6-a0f0-b66700b73686 · 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 Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 23

Resolution: metadata mismatch; local_arxiv, observed 2026-07-03T09:47:59.882874Z

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 cef66bdb-d22a-40e8-a56b-ae62af49193e · inbound

Linear Recurrent Unit with Semantic Modulation for Image Super-Resolution cites this paper.

Linear Recurrent Unit with Semantic Modulation for Image Super-Resolution Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-07-04T03:29:29.435897Z

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 56711364-b5c6-438f-b08b-655bbb5d52a3 · inbound

Tapered Language Models cites this paper.

Tapered Language Models Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-07-04T09:59:45.305176Z

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 df893389-7fa6-4dbe-bedc-a57a55a99500 · inbound

Harmonic: Hierarchical State Space Models for Efficient Long-Context Language Modeling cites this paper.

Harmonic: Hierarchical State Space Models for Efficient Long-Context Language Modeling Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 4

Resolution: metadata mismatch; local_arxiv, observed 2026-06-28T19:42:35.933085Z

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 fdc4b206-788c-4312-b5af-077c67d64a90 · inbound

SSM Adapters via Hankel Reduced-order Modeling: Injection Site Determines Task Suitability in Long-Context Fine-Tuning cites this paper.

SSM Adapters via Hankel Reduced-order Modeling: Injection Site Determines Task Suitability in Long-Context Fine-Tuning Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 1

Resolution: metadata mismatch; local_arxiv, observed 2026-07-04T15:19:56.025588Z

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 c128b580-bcc7-4126-b36b-bf9276309c66 · inbound

CARVE: Content-Aware Recurrent with Value Efficiency for Chunk-Parallel Linear Attention cites this paper.

CARVE: Content-Aware Recurrent with Value Efficiency for Chunk-Parallel Linear Attention Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 8

Resolution: metadata mismatch; local_arxiv, observed 2026-07-04T14:09:53.441851Z

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 2f81bd82-e038-42cd-a18e-3791e2cff5fd · inbound

CARVE: Content-Aware Recurrent with Value Efficiency for Chunk-Parallel Linear Attention cites this paper.

CARVE: Content-Aware Recurrent with Value Efficiency for Chunk-Parallel Linear Attention Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 8

Resolution: metadata mismatch; local_arxiv, observed 2026-06-30T09:44:37.449959Z

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 21955ff2-0e38-425b-9bf5-0f884c42ab49 · inbound

CARVE: Content-Aware Recurrent with Value Efficiency for Chunk-Parallel Linear Attention cites this paper.

CARVE: Content-Aware Recurrent with Value Efficiency for Chunk-Parallel Linear Attention Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-12T11:49:31.618283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c34e4da-8684-491b-b038-bd17202c16f6 · inbound

The Context-Ready Transformer cites this paper.

The Context-Ready Transformer Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 20

Resolution: metadata mismatch; local_arxiv, observed 2026-07-01T18:25:58.296712Z

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.