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Paper Citation Record · LEDGER

How Sparse Attention Approximates Exact Attention? Your Attention is Naturally $n^C$-Sparse

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2404.02690.

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

pith.paper-citation-record.v1
2404.02690 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T16:14:05.607282Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T14:43:22.563022Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 6b5812cf-0fcc-4015-8a02-991f2e04b931 · inbound

RetrievalAttention: Accelerating Long-Context LLM Inference via Vector Retrieval cites this paper.

RetrievalAttention: Accelerating Long-Context LLM Inference via Vector Retrieval How Sparse Attention Approximates Exact Attention? Your Attention is Naturally $n^C$-Sparse

Reference 61

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T08:12:02.011756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-05-18T08:12:01.798459Z digest=sha256:f971dcce0a866fd868f91089f0f5de60d1f6d7d554b579725cfc60a8e2da33ae

Observation 271fafd0-d81b-455e-a805-d2108fa7a407 · inbound

SCBench: A KV Cache-Centric Analysis of Long-Context Methods cites this paper.

SCBench: A KV Cache-Centric Analysis of Long-Context Methods How Sparse Attention Approximates Exact Attention? Your Attention is Naturally $n^C$-Sparse

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-11T16:14:05.607282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T16:14:05.607282Z digest=sha256:d6eb234ed69546166140046d0b32af9e0c9641d0c3c72c1cc2fa7cef7e7fd2bd

Observation 7efb6ab4-863e-4cb4-8da5-0ff89a75f6ff · inbound

HashAttention: Semantic Sparsity for Faster Inference cites this paper.

HashAttention: Semantic Sparsity for Faster Inference How Sparse Attention Approximates Exact Attention? Your Attention is Naturally $n^C$-Sparse

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-11T12:18:19.392692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:18:19.392692Z digest=sha256:399bf87884565e26a434e65816f870401d083809f8816eeed590b317e7720f32

Observation 5f031627-7f06-4564-8166-0c1a0750901d · inbound

LeMo: Enabling LEss Token Involvement for MOre Context Fine-tuning cites this paper.

LeMo: Enabling LEss Token Involvement for MOre Context Fine-tuning How Sparse Attention Approximates Exact Attention? Your Attention is Naturally $n^C$-Sparse

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-10T20:26:11.017792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:26:11.017792Z digest=sha256:c7641e62e2805944344ec5f2fe858e84a314aab1885966a2d4d19a2fdd96a5d2

Observation 6120744c-586e-439d-a8fd-b7678f16d20e · inbound

Video Latent Flow Matching: Optimal Polynomial Projections for Video Interpolation and Extrapolation cites this paper.

Video Latent Flow Matching: Optimal Polynomial Projections for Video Interpolation and Extrapolation How Sparse Attention Approximates Exact Attention? Your Attention is Naturally $n^C$-Sparse

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-09T18:51:12.401249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T18:51:12.401249Z digest=sha256:f132c801c55d5627e6d8c577836c9e585b2b7955876afbf0c6b0f92521876c3d

Observation 306b84cf-2d37-462e-b28a-8c935a3f14ce · inbound

RetroInfer: A Vector Storage Engine for Scalable Long-Context LLM Inference cites this paper.

RetroInfer: A Vector Storage Engine for Scalable Long-Context LLM Inference How Sparse Attention Approximates Exact Attention? Your Attention is Naturally $n^C$-Sparse

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-09T06:35:25.134551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-22T15:59:04.724780Z digest=sha256:6a7af2521efd1a8dd9b41600aaa43113f74ccc07a805aee2312064bef3902a1d

Observation 9b8de900-60eb-4bab-8ac4-71d127049db3 · inbound

SALE : Low-bit Estimation for Efficient Sparse Attention in Long-context LLM Prefilling cites this paper.

SALE : Low-bit Estimation for Efficient Sparse Attention in Long-context LLM Prefilling How Sparse Attention Approximates Exact Attention? Your Attention is Naturally $n^C$-Sparse

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T12:39:03.324221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:39:03.324221Z digest=sha256:8de845eb1d30f35920ec1276c4d96c279cc6c148a821c39a558cf5d6fd5ff1c0

Observation a6c6c0d2-b311-4656-a2ea-ccd32cfdedfb · inbound

EARN: Efficient Inference Acceleration for LLM-based Generative Recommendation by Register Tokens cites this paper.

EARN: Efficient Inference Acceleration for LLM-based Generative Recommendation by Register Tokens How Sparse Attention Approximates Exact Attention? Your Attention is Naturally $n^C$-Sparse

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T21:18:46.851223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:18:46.851223Z digest=sha256:1352a60fae95b41a7312714c9dbcec8a9e18dc4f3f280bd25eae90ced4ce7a55

Observation eff45d7b-c6ee-48fb-9095-99acb06129ed · inbound

DeltaLLM: A Training-Free Framework Exploiting Temporal Sparsity for Efficient Edge LLM Inference cites this paper.

DeltaLLM: A Training-Free Framework Exploiting Temporal Sparsity for Efficient Edge LLM Inference How Sparse Attention Approximates Exact Attention? Your Attention is Naturally $n^C$-Sparse

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T14:17:44.221622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:17:44.221622Z digest=sha256:dffb06f526d0fe2cf3781f44e4a523757838d4d27375c6f32ea1683363f21377

Observation 0bfba7ea-7231-457d-8cc2-e55107447ccd · inbound

Unifying Learning Dynamics and Generalization in Transformers Scaling Law cites this paper.

Unifying Learning Dynamics and Generalization in Transformers Scaling Law How Sparse Attention Approximates Exact Attention? Your Attention is Naturally $n^C$-Sparse

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-03T14:02:56.657443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T14:02:56.657443Z digest=sha256:37f8d6382a7a12b2c3b9cfd690ad634acc5517b9245e77b1725101715a7af97f

Observation 682b3543-8763-4ac2-ac00-c0bb4ecce3cd · inbound

AdaCluster: Adaptive Query-Key Clustering for Sparse Attention in Video Generation cites this paper.

AdaCluster: Adaptive Query-Key Clustering for Sparse Attention in Video Generation How Sparse Attention Approximates Exact Attention? Your Attention is Naturally $n^C$-Sparse

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-10T09:43:49.771996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-10T05:09:46.155328Z digest=sha256:24b764659561ae18a6c7d54b4760ec552e8f77a86d9c05336e7e7bbb29761dcf

Observation b8f0bd32-a0d4-457d-8005-c787e396ee0c · inbound

Unifying Sparse Attention with Hierarchical Memory for Scalable Long-Context LLM Serving cites this paper.

Unifying Sparse Attention with Hierarchical Memory for Scalable Long-Context LLM Serving How Sparse Attention Approximates Exact Attention? Your Attention is Naturally $n^C$-Sparse

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-12T09:01:25.970065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-07T13:15:21.201950Z digest=sha256:394b48d0f81870be7f258994691261b943798b48c73ecd028d5b24c359b1e8c3

Observation 7bd1e6bb-a2e3-4e1f-aade-e22b7ce1ed6c · inbound

Make Each Token Count: Towards Improving Long-Context Performance with KV Cache Eviction cites this paper.

Make Each Token Count: Towards Improving Long-Context Performance with KV Cache Eviction How Sparse Attention Approximates Exact Attention? Your Attention is Naturally $n^C$-Sparse

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-12T05:41:26.694598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-12T05:02:25.513351Z digest=sha256:7b5fbd74ade117f43ac1d664ad83824a2e39ce2b7007677053518a9e6c4bee69

Observation 270bd426-51b4-4746-9629-c86ccca39f24 · inbound

HierEdit: Region-Aware Hierarchical Diffusion for Efficient High-Resolution Editing cites this paper.

HierEdit: Region-Aware Hierarchical Diffusion for Efficient High-Resolution Editing How Sparse Attention Approximates Exact Attention? Your Attention is Naturally $n^C$-Sparse

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-20T14:43:22.565139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T14:40:20.517450Z digest=sha256:4fc8b1fe3a5278478df9191fa43d9ec36416c82d01292c97e4c6f8a87b1a2ab0

Observation 788cdefd-0f10-471b-b781-cc76670f2e2d · inbound

SPADE: An Input-Adaptive Sparse Attention Engine for Fast Video Diffusion Models Inference cites this paper.

SPADE: An Input-Adaptive Sparse Attention Engine for Fast Video Diffusion Models Inference How Sparse Attention Approximates Exact Attention? Your Attention is Naturally $n^C$-Sparse

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-05T20:50:03.960063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:50:03.960063Z digest=sha256:30cbfb9056add4edc9caf88f9f50674ce247583cc9911cd2459117b59f8167e0