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Paper Citation Record · LEDGER

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention

As of 5 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2607.24593.

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

pith.paper-citation-record.v1
2607.24593 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-31T11:04:04.591687Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

35 of 35 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved35
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f5b24f9d-cac6-4615-9f85-94c6b31ec424 · outbound

This paper cites DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models

Reference 1

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source=arxiv_source observed=2026-07-31T11:04:04.513448Z digest=sha256:a26ea860d45d54f966be7ee99752de404c1716f5980b476175168f17420da2c2

Observation d697f38f-c1f0-4ce2-adf2-895147bca37b · outbound

This paper cites HISA: Efficient Hierarchical Indexing for Fine-Grained Sparse Attention.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention HISA: Efficient Hierarchical Indexing for Fine-Grained Sparse Attention

Reference 2

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source=arxiv_source observed=2026-07-31T11:04:04.517513Z digest=sha256:a7da63f6ee567f77d447b665871cc21fabeb549581cf71da8e4736b198433d51

Observation e001cbac-c7c8-49de-813f-5d1f8739b938 · outbound

This paper cites arXiv preprint , year =.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention arXiv preprint , year =

Reference 3

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source=arxiv_source observed=2026-07-31T11:04:04.520125Z digest=sha256:daefb0c09685d87404cfa85283327e21e7df17cafca3eaf44ca8c4dd7a5f249d

Observation 5850cd51-bd3c-4300-8a02-6fa625e34ac2 · outbound

This paper cites arXiv preprint arXiv:2603.12201 , year =.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention arXiv preprint arXiv:2603.12201 , year =

Reference 4

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source=arxiv_source observed=2026-07-31T11:04:04.522372Z digest=sha256:9c257a370f4d17208c5f3a43feb116ce2d9eec90bd35c3da21b235628d0f8553

Observation 11414566-a211-4752-acaa-656bd0a0f56b · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention Advances in Neural Information Processing Systems , volume=

Reference 5

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source=arxiv_source observed=2026-07-31T11:04:04.524693Z digest=sha256:dcdaa353ad904a57a764583b3cd7021cb2e44c21b907e98eb978e54da07eb589

Observation 615534be-7122-4418-8206-4f466bc122a5 · outbound

This paper cites FlexPrefill: A Context-Aware Sparse Attention Mechanism for Efficient Long-Sequence Inference.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention FlexPrefill: A Context-Aware Sparse Attention Mechanism for Efficient Long-Sequence Inference

Reference 6

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source=arxiv_source observed=2026-07-31T11:04:04.526969Z digest=sha256:77c872a8904d41ca9035cfc717625b23d403a7d17830fed64ec109c8c1cd0e2c

Observation 51fcd71d-befb-4202-ac04-25aed211ea33 · outbound

This paper cites XAttention: Block Sparse Attention with Antidiagonal Scoring.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention XAttention: Block Sparse Attention with Antidiagonal Scoring

Reference 7

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source=arxiv_source observed=2026-07-31T11:04:04.529750Z digest=sha256:900eb3d2e18135f128a04c3d5c73237ebc7fbbd4926f29390a06d20806847889

Observation 59aba606-4570-4574-8eb9-a9b4061065c8 · outbound

This paper cites MoBA: Mixture of Block Attention for Long-Context LLMs.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention MoBA: Mixture of Block Attention for Long-Context LLMs

Reference 8

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source=arxiv_source observed=2026-07-31T11:04:04.532117Z digest=sha256:2081a92dbfe269ed2b5d766680d83ab5ecdcbce33c58fa29e96881b366ad0a48

Observation 838a464e-1e50-4607-8d35-f5a80d2fa7b8 · outbound

This paper cites Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 9

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source=arxiv_source observed=2026-07-31T11:04:04.534536Z digest=sha256:4c987fb1178b63d36985135624dcc714f7277169588cc9adc45199adb93baff6

Observation 1f3360d4-b79e-4188-8e35-ceb5c3872d29 · outbound

This paper cites arXiv preprint arXiv:2603.06274 , year=.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention arXiv preprint arXiv:2603.06274 , year=

Reference 10

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source=arxiv_source observed=2026-07-31T11:04:04.536683Z digest=sha256:19a0cef67b8144beb9a839de1066b53a9e7885dcf2b6384b313b6c2dde3be028

Observation ec0f7d09-cb78-4a40-a4ec-8285c62a8ff6 · outbound

This paper cites LazyLLM: Dynamic Token Pruning for Efficient Long Context LLM Inference.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention LazyLLM: Dynamic Token Pruning for Efficient Long Context LLM Inference

Reference 11

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source=arxiv_source observed=2026-07-31T11:04:04.538729Z digest=sha256:5292cac18a492199e489dec582cb407633b3471fa6ac3bc5add4e1c4617ad14a

Observation 60aa39bc-da1b-49f3-bad3-f940605cb2e3 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention Advances in Neural Information Processing Systems , volume=

Reference 12

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source=arxiv_source observed=2026-07-31T11:04:04.541061Z digest=sha256:0283e1999175a5210e07839dd25e4a43bc1eb20301fca41b73427e79c869cb2d

Observation bd86e0ae-07d9-4d56-941c-d3917dae9a68 · outbound

This paper cites Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing , pages=.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing , pages=

Reference 13

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source=arxiv_source observed=2026-07-31T11:04:04.543095Z digest=sha256:09cd16484c39addf03ae23675276108c661cfe66e2f7c452267f133f7ff55543

Observation fc6ae7ef-02eb-440a-8d69-f720f25b3684 · outbound

This paper cites 2024 , eprint=.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention 2024 , eprint=

Reference 14

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source=arxiv_source observed=2026-07-31T11:04:04.546121Z digest=sha256:489093de79d0ac492965ede159302ace6c9e7cd6a262e0a1d37ffc8b6a0316f0

Observation 529fc8b3-111b-436a-8bbe-32566a58c635 · outbound

This paper cites GLM-5: from Vibe Coding to Agentic Engineering.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention GLM-5: from Vibe Coding to Agentic Engineering

Reference 15

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source=arxiv_source observed=2026-07-31T11:04:04.548222Z digest=sha256:acfbc22ae250c093d30e928c62ce4617ce75173bd510006d04abafb8894e03e5

Observation 6fa48edc-3045-492d-bd38-e27021e1eafe · outbound

This paper cites Proceedings of the 62nd annual meeting of the association for computational linguistics (volume 1: Long papers) , pages=.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention Proceedings of the 62nd annual meeting of the association for computational linguistics (volume 1: Long papers) , pages=

Reference 16

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source=arxiv_source observed=2026-07-31T11:04:04.550453Z digest=sha256:3869d735e480c63e8445e1055a2171a463ed8c1d122a2cb2bbde2759aa9873b0

Observation fd82159f-171e-4464-ba0a-b3850e98cb01 · outbound

This paper cites Annual Meeting of the Association for Computational Linguistics (ACL) , year =.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention Annual Meeting of the Association for Computational Linguistics (ACL) , year =

Reference 17

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source=arxiv_source observed=2026-07-31T11:04:04.552295Z digest=sha256:42e52b0592a889f0cdbf91e9516b5af59e1aa3fb6d2e94c86e5ba803497e8980

Observation a33ac9d3-315e-48df-8ea6-70c3e551d9f0 · outbound

This paper cites RULER: What's the Real Context Size of Your Long-Context Language Models?.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention RULER: What's the Real Context Size of Your Long-Context Language Models?

Reference 18

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source=arxiv_source observed=2026-07-31T11:04:04.554289Z digest=sha256:180accb8f1b2703dc6f9d745611d72537078e9579b07238de6d96151d962679f

Observation 8722fe95-a255-41d6-9ba5-cc823a669c2d · outbound

This paper cites Proceedings of the 29th Symposium on Operating Systems Principles (SOSP) , year =.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention Proceedings of the 29th Symposium on Operating Systems Principles (SOSP) , year =

Reference 19

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source=arxiv_source observed=2026-07-31T11:04:04.556473Z digest=sha256:702c9fb91e8b16aaa41419cc2f06854adba0e45b2a8980596994e2b0102ec01e

Observation e17c3b08-9cde-4284-bb7a-3f2e8dd642e0 · outbound

This paper cites an unresolved cited work.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention Unresolved cited work

Reference 20

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source=arxiv_source observed=2026-07-31T11:04:04.558523Z digest=sha256:d2b5dc65cd6404e6923b29945a38d87ccbc603e435cfb4d49de0aa68d83d8f90

Observation ea4defef-a86c-432e-8ace-22542cefc9dc · outbound

This paper cites int8 (): 8-bit matrix multiplication for transformers at scale , author=.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention int8 (): 8-bit matrix multiplication for transformers at scale , author=

Reference 21

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source=arxiv_source observed=2026-07-31T11:04:04.560504Z digest=sha256:fb2181da8cb2e629fef3200d844ace8de0660cd9e8f2ffff7b379e9a50879d77

Observation 62bead20-80b3-4e12-a418-4b7253b61019 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 22

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source=arxiv_source observed=2026-07-31T11:04:04.562507Z digest=sha256:e7cd72fc26c6e983a53b1fbe98c3901dd302c571e47b67e4d34f688a38ec79da

Observation da9c64c8-a41a-4133-8b40-a97e5539efca · outbound

This paper cites Qwen3 Technical Report.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention Qwen3 Technical Report

Reference 23

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source=arxiv_source observed=2026-07-31T11:04:04.564666Z digest=sha256:286fdba5a804929d5003f9462878768261c4ee4cf00a882cfa710fac1e957f4b

Observation 1faed358-89f8-4158-9fd6-86fc405e42b1 · outbound

This paper cites International conference on algorithmic learning theory , pages=.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention International conference on algorithmic learning theory , pages=

Reference 24

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source=arxiv_source observed=2026-07-31T11:04:04.566891Z digest=sha256:0afb8333ba61694e533c1523831a11e08595fe74314103947efc80c1439aa224

Observation 68b4bd60-4ad1-41d1-b6af-632a4bbdadf5 · outbound

This paper cites Kimi K2: Open Agentic Intelligence.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention Kimi K2: Open Agentic Intelligence

Reference 25

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source=arxiv_source observed=2026-07-31T11:04:04.569004Z digest=sha256:ae84058e0b8c5f8c70f8701080f0782b91ea23abdbf1f58a5e22eb2ccf692b0f

Observation d7cf0e14-d605-43d8-9695-59c2a54a749a · outbound

This paper cites arXiv preprint arXiv:2509.24663 , year=.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention arXiv preprint arXiv:2509.24663 , year=

Reference 26

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source=arxiv_source observed=2026-07-31T11:04:04.571340Z digest=sha256:2241e2f9d9166084483bb2e823696b5329690ebb40dde95db7497e8b3744071d

Observation 47c3b097-9b55-4159-93c0-d87eeee41ec0 · outbound

This paper cites arXiv preprint arXiv:2602.03560 , year=.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention arXiv preprint arXiv:2602.03560 , year=

Reference 27

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source=arxiv_source observed=2026-07-31T11:04:04.573511Z digest=sha256:557ebe930fa2b65d524aac5e0fe1e27124b55ff5d993223204bdd1ba961c866a

Observation 4fcbc682-8a47-4590-90bd-2401f0776dae · outbound

This paper cites International Conference on Learning Representations , volume=.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention International Conference on Learning Representations , volume=

Reference 28

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source=arxiv_source observed=2026-07-31T11:04:04.575512Z digest=sha256:6c1cd927f4b01f7d5f40d08b9bb54b769a3ca71ad3c7c6a51cb5cc5a06e1e6c1

Observation 94eebb90-568f-45ec-a046-864ec081f201 · outbound

This paper cites arXiv preprint arXiv:2509.24745 , year=.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention arXiv preprint arXiv:2509.24745 , year=

Reference 29

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source=arxiv_source observed=2026-07-31T11:04:04.577595Z digest=sha256:76dbe593bb5c49010406b0f9e3cc282e5b5466a15ed153b70f1e32c9199f55b8

Observation fb9c76ae-c1f1-4464-b8aa-2b608a2e0421 · outbound

This paper cites SeerAttention: Learning Intrinsic Sparse Attention in Your LLMs.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention SeerAttention: Learning Intrinsic Sparse Attention in Your LLMs

Reference 30

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source=arxiv_source observed=2026-07-31T11:04:04.579723Z digest=sha256:c3bf6f394aa9e91c3636aeb00f5c347c46194c2481f9ec7aec618f7e52149ab6

Observation 8bb9cb9a-5b29-467e-b518-3caf6038c74c · outbound

This paper cites SparDA: Sparse Decoupled Attention for Efficient Long-Context LLM Inference.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention SparDA: Sparse Decoupled Attention for Efficient Long-Context LLM Inference

Reference 31

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source=arxiv_source observed=2026-07-31T11:04:04.582053Z digest=sha256:7db50b2b47c24a457ed5aeb58c7bba6e078d60292b79f6677f7cbbe2629f7fdf

Observation 5ee18d25-c704-4b04-9543-64c33b112150 · outbound

This paper cites SeerAttention-R: Sparse Attention Adaptation for Long Reasoning.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention SeerAttention-R: Sparse Attention Adaptation for Long Reasoning

Reference 32

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source=arxiv_source observed=2026-07-31T11:04:04.584216Z digest=sha256:71c247b8e33ad44d5a7ee51e26567eb143ab460bf6fef63f40fd3f41c734f75e

Observation ee1f1960-9c4a-4ef6-ba97-63858619af08 · outbound

This paper cites Full Attention Strikes Back: Transferring Full Attention into Sparse within Hundred Training Steps.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention Full Attention Strikes Back: Transferring Full Attention into Sparse within Hundred Training Steps

Reference 33

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source=arxiv_source observed=2026-07-31T11:04:04.586667Z digest=sha256:a9c34a933af3cb757c2501932ce2e8ec6c829689fbea510050d7b43359d7d159

Observation 284e5753-3ba2-4d82-a1bb-310cb2ee18f0 · outbound

This paper cites MiMo: Unlocking the Reasoning Potential of Language Model -- From Pretraining to Posttraining.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention MiMo: Unlocking the Reasoning Potential of Language Model -- From Pretraining to Posttraining

Reference 34

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source=arxiv_source observed=2026-07-31T11:04:04.589430Z digest=sha256:8695245bf22498cf4b7da48e9f114dfcb01fb3d4720bfceb6e55043821731784

Observation eb91c79e-9676-4e67-b63f-7dfaed4ce0fd · outbound

This paper cites Quest: Query-Aware Sparsity for Efficient Long-Context LLM Inference.

PIVOT: Efficient Query-Group Indexing for Token-Level Sparse Attention Quest: Query-Aware Sparsity for Efficient Long-Context LLM Inference

Reference 35

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source=arxiv_source observed=2026-07-31T11:04:04.591687Z digest=sha256:090dc39bd8c821ea6a0f19932a005cf2d3898b1a81aab4897998fcd27ee218ad

Pith citing papers

No inbound Pith citation observations are available.