Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-27T13:18:18.331031Z
Paper Citation Record · LEDGER
Dynamic Linear Attention
As of 9 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2606.10650.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
28 of 28 outbound references displayed
- verified exact8
- verified fuzzy0
- unresolved18
- parse uncertain0
- malformed identifier0
- metadata mismatch2
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation bf4af32d-1f4e-4508-8baf-1ea91200213a · outbound
This paper cites Efficient Large Language Models: A Survey.
Dynamic Linear Attention Efficient Large Language Models: A Survey
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T05:27:39.795371Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 6bd91c5c-615c-4edd-a806-dfd06e9a4ac7 · outbound
This paper cites The Internet of Things in the Era of Generative AI: Vision and Challenges.
Dynamic Linear Attention The Internet of Things in the Era of Generative AI: Vision and Challenges
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T05:27:39.803407Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation a77c7bc3-5ca6-49e7-bf5f-1bfed029da4d · outbound
This paper cites D2O: dynamic discriminative operations for efficient long-context inference of large language models.
Dynamic Linear Attention D2O: dynamic discriminative operations for efficient long-context inference of large language models
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T13:18:18.331031Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 36fbe125-92d3-45c4-b5cd-8fae184dd0c1 · outbound
This paper cites Parallelizing linear transformers with the delta rule over sequence length.
Dynamic Linear Attention Parallelizing linear transformers with the delta rule over sequence length
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T13:18:18.331031Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 625553e2-6a4d-4c38-90ce-896250d76c28 · outbound
This paper cites Gated delta networks: Improving mamba2 with delta rule.
Dynamic Linear Attention Gated delta networks: Improving mamba2 with delta rule
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T13:18:18.331031Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 90562a5c-5c05-45f2-9c6c-b8e5dfd096e9 · outbound
This paper cites Log-linear attention.
Dynamic Linear Attention Log-linear attention
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T05:27:39.805845Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation ff44463c-5200-4e82-9e62-0fdd9a95fc3a · outbound
This paper cites Rat: Bridging rnn efficiency and attention accuracy via chunk-based sequence modeling.arXiv preprint arXiv:2507.04416.
Dynamic Linear Attention Rat: Bridging rnn efficiency and attention accuracy via chunk-based sequence modeling.arXiv preprint arXiv:2507.04416
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T05:27:39.808242Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 54974d42-43be-4111-bf3a-8fdeb80fc1b2 · outbound
This paper cites Generalizing the Cauchy-Schwarz inequality: Hadamard powers and tensor products.
Dynamic Linear Attention Generalizing the Cauchy-Schwarz inequality: Hadamard powers and tensor products
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T05:27:39.811665Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 4773cfe9-f931-43a1-a442-9665796f4bfd · outbound
This paper cites Kandula, S.
Dynamic Linear Attention Kandula, S
Reference 9
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-27T13:20:56.498542Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 016d5bc2-a160-47d3-b5e8-d97d950a6ea2 · outbound
This paper cites Transformers are ssms: Generalized models and efficient algorithms through structured state space duality.
Dynamic Linear Attention Transformers are ssms: Generalized models and efficient algorithms through structured state space duality
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T13:18:18.331031Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 90d8747d-add1-4450-8852-d819d4bc853f · outbound
This paper cites The LAMBADA dataset: Word prediction requiring a broad discourse context.
Dynamic Linear Attention The LAMBADA dataset: Word prediction requiring a broad discourse context
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T13:18:18.331031Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8fff127f-341d-4211-91a6-71ebb0b55dfb · outbound
This paper cites PIQA: reasoning about physical commonsense in natural language.
Dynamic Linear Attention PIQA: reasoning about physical commonsense in natural language
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T13:18:18.331031Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 84aabda0-5d25-4bef-80aa-bebdb09d8771 · outbound
This paper cites Hellaswag: Can a machine really finish your sentence? InACL (1), pages 4791–4800.
Dynamic Linear Attention Hellaswag: Can a machine really finish your sentence? InACL (1), pages 4791–4800
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T13:18:18.331031Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 06cfc6b1-ffe1-490e-8a13-5b680f82e7e3 · outbound
This paper cites Winogrande: an adversarial winograd schema challenge at scale.Commun.
Dynamic Linear Attention Winogrande: an adversarial winograd schema challenge at scale.Commun
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T13:18:18.331031Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation adfc1108-4f06-4c79-8f2c-de0b5bff0f16 · outbound
This paper cites Can a suit of armor conduct electricity? A new dataset for open book question answering.
Dynamic Linear Attention Can a suit of armor conduct electricity? A new dataset for open book question answering
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T13:18:18.331031Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 053248d3-f82e-4270-adb1-324ff19527fc · outbound
This paper cites Commonsenseqa: A question answering challenge targeting commonsense knowledge.
Dynamic Linear Attention Commonsenseqa: A question answering challenge targeting commonsense knowledge
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T13:18:18.331031Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation badf0a94-f75a-4475-b5d9-a3f734903f01 · outbound
This paper cites Think you have Solved Direct-Answer Question Answering? Try ARC-DA, the Direct-Answer AI2 Reasoning Challenge.
Dynamic Linear Attention Think you have Solved Direct-Answer Question Answering? Try ARC-DA, the Direct-Answer AI2 Reasoning Challenge
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T05:27:39.814497Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 6bf6d3b0-eaf7-446c-81c3-bee219b26ccd · outbound
This paper cites Openceres: When open information extraction meets the semi-structured web.
Dynamic Linear Attention Openceres: When open information extraction meets the semi-structured web
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T13:18:18.331031Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0f905f97-44c3-448a-9fce-3133cf7905a8 · outbound
This paper cites Know what you don’t know: Unanswerable questions for squad.
Dynamic Linear Attention Know what you don’t know: Unanswerable questions for squad
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T13:18:18.331031Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3cc1bd67-358b-40c3-9db4-da6f16386fab · outbound
This paper cites Language models enable simple systems for generating structured views of heterogeneous data lakes.
Dynamic Linear Attention Language models enable simple systems for generating structured views of heterogeneous data lakes
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T13:18:18.331031Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3937c890-a687-4f70-a02c-8708638c0379 · outbound
This paper cites Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension.
Dynamic Linear Attention Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T13:18:18.331031Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5f65e2be-a459-4b7e-810f-645333d6221f · outbound
This paper cites Drop: A reading comprehension benchmark requiring discrete reasoning over paragraphs.
Dynamic Linear Attention Drop: A reading comprehension benchmark requiring discrete reasoning over paragraphs
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T13:18:18.331031Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5938956f-fd71-4e2e-9b68-2d2a1a3a9879 · outbound
This paper cites Natural questions: a benchmark for question answering research.
Dynamic Linear Attention Natural questions: a benchmark for question answering research
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T13:18:18.331031Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cd79f933-d1d7-46da-b0f9-7c3e2fb5e1b8 · outbound
This paper cites RULER: What's the Real Context Size of Your Long-Context Language Models?.
Dynamic Linear Attention RULER: What's the Real Context Size of Your Long-Context Language Models?
Reference 24
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T05:27:39.809094Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 447853f9-fd8a-48e1-a7f1-9952f0184784 · outbound
This paper cites Longbench: A bilingual, multitask benchmark for long context understanding.
Dynamic Linear Attention Longbench: A bilingual, multitask benchmark for long context understanding
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T13:18:18.331031Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 583c6f59-8681-4a98-a4e0-24f35b1a4312 · outbound
This paper cites He, B., Yin, L., Zhen, H.-L., Liu, S., Wu, H., Zhang, X., Yuan, M., and Ma, C.
Dynamic Linear Attention He, B., Yin, L., Zhen, H.-L., Liu, S., Wu, H., Zhang, X., Yuan, M., and Ma, C
Reference 26
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-03T05:27:39.813686Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation b64b2ac2-527e-4c50-9608-7eccaacb0934 · outbound
This paper cites Simple linear attention language models balance the recall-throughput tradeoff.
Dynamic Linear Attention Simple linear attention language models balance the recall-throughput tradeoff
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-06-27T13:18:18.331031Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fe41f40b-c4eb-4e33-9c66-88efee403781 · outbound
This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.
Dynamic Linear Attention Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Reference 28
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T05:27:39.806518Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Pith citing papers
No inbound Pith citation observations are available.