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Paper Citation Record · LEDGER

Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:2401.04658.

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

pith.paper-citation-record.v1
2401.04658 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 18 of 18 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 18 of 18 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:44:50.687143Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation c2f4e469-cf29-4ec6-81df-2559fb36797b · 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 Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-23T18:33:19.483122Z

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=2026-05-23T18:31:35.391674Z digest=sha256:9d830525642d842606ae56f8d6f74154a7ab8a7d387c4de6f9e5f7288ac42f06

Observation 34b89f3c-8c5e-482f-a8a0-c935734b2667 · inbound

SageAttention2++: A More Efficient Implementation of SageAttention2 cites this paper.

SageAttention2++: A More Efficient Implementation of SageAttention2 Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models

Reference 2016

Resolution
unresolved
no resolver link, observed 2026-08-07T13:44:50.687143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:44:50.687143Z digest=sha256:58623fce240f1924b13804340bff5c1616547d7c10480b1f199cb69ee5cb1739

Observation 210f87e3-5250-4913-835f-ce77de68d1b6 · inbound

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

AuroraLong: Bringing RNNs Back to Efficient Open-Ended Video Understanding Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-06T20:29:53.778431Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:29:53.778431Z digest=sha256:3258f13daf2e5a93e1bda01ce790e00a7e23c7655aef2988a742c589c0a7bc2d

Observation 4417498f-24f2-49bf-9455-b66670c7696b · inbound

DistrAttention: An Efficient and Flexible Self-Attention Mechanism on Modern GPUs cites this paper.

DistrAttention: An Efficient and Flexible Self-Attention Mechanism on Modern GPUs Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-06T14:59:20.274728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:59:20.274728Z digest=sha256:e1d595e7e41e159bbbdc17f914bcd0f9e462b8d82a4f44800b1c567bc6ac3bb9

Observation 1ab9bc81-4ff8-4e94-9e55-4dc7078412fd · inbound

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

Hybrid Architectures for Language Models: Systematic Analysis and Design Insights Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-05-18T10:21:15.061486Z

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=2026-05-18T10:18:04.431436Z digest=sha256:66415c1a718ec5f46b7de86335764887c41209bce4235cc7a88a922982e828f2

Observation dd382d08-9c0c-4a57-b0f0-d3738fb1b59a · inbound

Higher-order Linear Attention cites this paper.

Higher-order Linear Attention Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-18T03:05:47.382651Z

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=2026-05-18T03:05:35.823369Z digest=sha256:c6fee4f7bc6e2fa3c2ace462e58d7a64a035c82836e12b2fe9ab60fd37451ae5

Observation bbf7b08b-9b95-402f-94d8-f88925d89b30 · inbound

Memory in the Age of AI Agents cites this paper.

Memory in the Age of AI Agents Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-11T18:18:20.163987Z

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=2026-05-11T18:18:19.911342Z digest=sha256:8a17861e7d9bb71fcfb71737edc749cfaa8788a5c56d53ca72886debf79bf0c8

Observation 3065605d-6d66-4b14-b76f-0514b71f8d99 · inbound

On The Application of Linear Attention in Multimodal Transformers cites this paper.

On The Application of Linear Attention in Multimodal Transformers Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-11T07:20:59.526297Z

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=2026-05-10T17:12:49.695614Z digest=sha256:f080009a5486272c49a671d5a52ba1b100212acedeacb8fc44b06522a3d083d7

Observation 18579422-e733-4de1-88c4-2a17a8c7df5b · inbound

Long-Context Aware Upcycling: A New Frontier for Hybrid LLM Scaling cites this paper.

Long-Context Aware Upcycling: A New Frontier for Hybrid LLM Scaling Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-11T22:01:10.671459Z

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=2026-05-08T03:39:37.485602Z digest=sha256:075785ffe86e781dd16056d76ed8e8eaf29f94d54355cfa00f6fad12aab927b7

Observation 682016e4-3e7f-45a6-8a2f-8379c78b9b59 · inbound

Adaptive Memory Decay for Log-Linear Attention cites this paper.

Adaptive Memory Decay for Log-Linear Attention Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models

Reference 14

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T04:50:56.380655Z

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=2026-05-11T01:02:56.848785Z digest=sha256:43826f8371e48743f547fad748aebf5e1e6ccbf8549f1af60050f388e8cd95b6

Observation fa0b417a-bda2-4b71-ba44-4fc0ae69d3f4 · inbound

ThriftAttention: Selective Mixed Precision for Long-Context FP4 Attention cites this paper.

ThriftAttention: Selective Mixed Precision for Long-Context FP4 Attention Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:30:22.840962Z

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=2026-05-25T05:28:40.888215Z digest=sha256:f62d87743bfbec13f13e80654ada83676ed218c14fe347035a301b0a218f540b

Observation ecbae65f-9ade-4f20-a27c-0b70ebf09afc · inbound

Dynamic Short Convolutions Improve Transformers cites this paper.

Dynamic Short Convolutions Improve Transformers Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models

Reference 87

Resolution
verified exact
arxiv_id, observed 2026-07-02T02:36:27.012767Z

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=sha256:828d032163bd1452cf0ce73980a3148dd092358f2c86f2aadc8b557ddd7b0511

Observation d7fabafa-d1f5-400e-9d54-9a99635e3c7f · 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 Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-07-03T09:47:59.878110Z

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:bd3354467b94daa5a82a5be3526482d788607edf2c9cab153fe6a89047b3bc09

Observation 90107221-b4ec-47be-946d-3037a2b38362 · inbound

Physics-Informed Neural Network with Squeeze-Excitation-like Attention cites this paper.

Physics-Informed Neural Network with Squeeze-Excitation-like Attention Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models

Reference 57

Resolution
verified exact
arxiv_id, observed 2026-07-04T03:29:30.199130Z

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=2026-06-26T18:02:39.721547Z digest=sha256:0796e25b683f80a2e3ed1aa2944240bc26710c41677c10ac74e00ccf35919887

Observation 375ebb43-7efb-4d36-8eec-854e9478d337 · inbound

Morphing into Hybrid Attention Models cites this paper.

Morphing into Hybrid Attention Models Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-06-30T08:44:28.072509Z

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=sha256:8461174e07f093ddc26e0805bcbb8f4f8faa6805eab541866c1aeb120d9123f5

Observation 0ba81ed1-a556-4cdd-b9e0-1437a75629f7 · inbound

HYPIC: Accelerating Hybrid-Attention LLM Serving with Position-Independent Caching cites this paper.

HYPIC: Accelerating Hybrid-Attention LLM Serving with Position-Independent Caching Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-07-03T18:58:50.719338Z

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=2026-07-03T18:53:12.126023Z digest=sha256:59cbb932b1b52bbcbc43fa50d8f90a43ca3713872b32011636c0fe5ca807f3d2

Observation 4988e43d-14e9-4bfe-8888-c123aa8877ca · inbound

HYPIC: Accelerating Hybrid-Attention LLM Serving with Position-Independent Caching cites this paper.

HYPIC: Accelerating Hybrid-Attention LLM Serving with Position-Independent Caching Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models

Reference 34

Resolution
unresolved
no resolver link, observed 2026-07-14T16:49:27.301911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T16:49:27.301911Z digest=sha256:e3c4d8d3bb2c50ffa0f1bfc0dbf9abcea5f5cb46a07a0034b861407a2522e766

Observation 36ba925c-029b-4b53-afd1-c6e80ab1e360 · inbound

Ring-Zero: Scaling Zero RL to a Trillion Parameters for Emergent Reasoning cites this paper.

Ring-Zero: Scaling Zero RL to a Trillion Parameters for Emergent Reasoning Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-02T06:37:38.357406Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T06:37:38.357406Z digest=sha256:1c6dcb79f113ab66d51bad5d684db338f6ef73a1afde7b1d124f863bca433bb7