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Paper Citation Record · LEDGER

Lag-Relative Sparse Attention In Long Context Training

As of 8 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2506.11498.

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

pith.paper-citation-record.v1
2506.11498 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:10:50.032662Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

38 of 38 outbound references displayed

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  • verified fuzzy5
  • unresolved32
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External citation measurements

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Outbound references

Observation 8e0c89a8-6963-4fab-8847-878f1383cd32 · outbound

This paper cites Longformer: The Long-Document Transformer.

Lag-Relative Sparse Attention In Long Context Training Longformer: The Long-Document Transformer

Reference 1

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Observation 99f00575-4a14-4f4f-b684-39292ea5e963 · outbound

This paper cites ACM transactions on intelligent systems and technology15(3), 1–45 (2024).

Lag-Relative Sparse Attention In Long Context Training ACM transactions on intelligent systems and technology15(3), 1–45 (2024)

Reference 2

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Observation 9858e872-dc4e-49fb-acb1-162b3f78f323 · outbound

This paper cites Generating Long Sequences with Sparse Transformers.

Lag-Relative Sparse Attention In Long Context Training Generating Long Sequences with Sparse Transformers

Reference 3

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Observation 660f74f3-918e-4453-87f1-ee55c3ffde2f · outbound

This paper cites Advances in neural information pro- cessing systems35, 16344–16359 (2022).

Lag-Relative Sparse Attention In Long Context Training Advances in neural information pro- cessing systems35, 16344–16359 (2022)

Reference 4

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Observation a11b3d47-cc92-4d8e-833a-c9f2cb615b2c · outbound

This paper cites LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens.

Lag-Relative Sparse Attention In Long Context Training LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens

Reference 5

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Observation 951d4d05-8915-4e9d-8769-0451d3550c08 · outbound

This paper cites Ada-KV: Optimizing KV Cache Eviction by Adaptive Budget Allocation for Efficient LLM Inference.

Lag-Relative Sparse Attention In Long Context Training Ada-KV: Optimizing KV Cache Eviction by Adaptive Budget Allocation for Efficient LLM Inference

Reference 6

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Observation 453bb1dc-f0de-4956-8038-2d0652d1c99a · outbound

This paper cites Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs.

Lag-Relative Sparse Attention In Long Context Training Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs

Reference 7

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Observation 072bec5e-41b3-4ba7-987b-b09d19c14c40 · outbound

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

Lag-Relative Sparse Attention In Long Context Training RULER: What's the Real Context Size of Your Long-Context Language Models?

Reference 8

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Observation fd22ae9b-fc94-4c64-b8be-ada4766b70af · outbound

This paper cites an unresolved cited work.

Lag-Relative Sparse Attention In Long Context Training Unresolved cited work

Reference 9

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Observation 17a278f5-ba27-41f6-b918-962f6bd530f4 · outbound

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

Lag-Relative Sparse Attention In Long Context Training FlexPrefill: A Context-Aware Sparse Attention Mechanism for Efficient Long-Sequence Inference

Reference 10

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Observation 95d69890-e773-4016-9ffe-e21d987ac112 · outbound

This paper cites In: Proceedings of the AAAI Conference on Artificial Intelligence.

Lag-Relative Sparse Attention In Long Context Training In: Proceedings of the AAAI Conference on Artificial Intelligence

Reference 11

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Observation f1ade16f-2c92-4fc1-b178-ac781e464afe · outbound

This paper cites A Survey on Large Language Model Acceleration based on KV Cache Management.

Lag-Relative Sparse Attention In Long Context Training A Survey on Large Language Model Acceleration based on KV Cache Management

Reference 12

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Observation 7901cc6a-1c85-4958-89de-9a23092d9d9e · outbound

This paper cites In: International Conference on Machine Learning.

Lag-Relative Sparse Attention In Long Context Training In: International Conference on Machine Learning

Reference 13

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Observation e5d9f31e-b613-4a3c-8b4c-a3c8fbe621df · outbound

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

Lag-Relative Sparse Attention In Long Context Training SCBench: A KV Cache-Centric Analysis of Long-Context Methods

Reference 14

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Observation 1a340d0c-bd4d-4793-811b-b66cfa7953fb · outbound

This paper cites Advances in Neural Information Processing Systems37, 22947–22970 (2024).

Lag-Relative Sparse Attention In Long Context Training Advances in Neural Information Processing Systems37, 22947–22970 (2024)

Reference 15

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Observation 0d54b903-c43e-4757-82b3-b28368f6f2de · outbound

This paper cites LagKV: Lag-Relative Information of the KV Cache Tells Which Tokens Are Important.

Lag-Relative Sparse Attention In Long Context Training LagKV: Lag-Relative Information of the KV Cache Tells Which Tokens Are Important

Reference 16

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Observation 74c5279a-4547-4804-89d1-cc6e734aca02 · outbound

This paper cites Advances in Neural Information Processing Systems36, 52342–52364 (2023).

Lag-Relative Sparse Attention In Long Context Training Advances in Neural Information Processing Systems36, 52342–52364 (2023)

Reference 17

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation f8b4264f-0eee-4127-9039-d2956b12d165 · outbound

This paper cites Decoupled Weight Decay Regularization.

Lag-Relative Sparse Attention In Long Context Training Decoupled Weight Decay Regularization

Reference 18

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Observation b7b9b8d8-57db-4204-8c37-c22797ae4e76 · outbound

This paper cites Sparser is Faster and Less is More: Efficient Sparse Attention for Long-Range Transformers.

Lag-Relative Sparse Attention In Long Context Training Sparser is Faster and Less is More: Efficient Sparse Attention for Long-Range Transformers

Reference 19

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Observation 7d81b4e5-93ba-42e7-82ec-1d5060865a47 · outbound

This paper cites A Comprehensive Overview of Large Language Models.

Lag-Relative Sparse Attention In Long Context Training A Comprehensive Overview of Large Language Models

Reference 20

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Observation 9ee3ff58-ddc7-43ba-affe-fd86f9d17363 · outbound

This paper cites an unresolved cited work.

Lag-Relative Sparse Attention In Long Context Training Unresolved cited work

Reference 21

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Observation 43ee4ba6-d273-4641-aa4f-ee72187c57da · outbound

This paper cites an unresolved cited work.

Lag-Relative Sparse Attention In Long Context Training Unresolved cited work

Reference 22

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Observation 49707010-7876-4cd1-8929-f6a69f522c32 · outbound

This paper cites YaRN: Efficient Context Window Extension of Large Language Models.

Lag-Relative Sparse Attention In Long Context Training YaRN: Efficient Context Window Extension of Large Language Models

Reference 23

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Observation cf6665d2-74a0-4dc7-b880-d861afc4a0dc · outbound

This paper cites Qwen2.5 Technical Report.

Lag-Relative Sparse Attention In Long Context Training Qwen2.5 Technical Report

Reference 24

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Observation 2af3c4f5-3cbd-4259-842a-853b4e637f71 · outbound

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

Lag-Relative Sparse Attention In Long Context Training Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism

Reference 25

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Observation 8c335968-fa1d-4fa6-b2bd-1cc67049f5a7 · outbound

This paper cites Neurocomputing568, 127063 (2024).

Lag-Relative Sparse Attention In Long Context Training Neurocomputing568, 127063 (2024)

Reference 26

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Observation 7498beaa-71fc-4113-8280-c9aa8c69579d · outbound

This paper cites TokenCarve: Information-Preserving Visual Token Compression in Multimodal Large Language Models.

Lag-Relative Sparse Attention In Long Context Training TokenCarve: Information-Preserving Visual Token Compression in Multimodal Large Language Models

Reference 27

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Observation 49883b0e-1ec7-4da8-8c75-11935e0ed8b1 · outbound

This paper cites RazorAttention: Efficient KV Cache Compression Through Retrieval Heads.

Lag-Relative Sparse Attention In Long Context Training RazorAttention: Efficient KV Cache Compression Through Retrieval Heads

Reference 28

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Observation f95ac60f-4d6d-42e5-bc00-ac612b3132e9 · outbound

This paper cites In: Proceedings of the 41st Inter- national Conference on Machine Learning.

Lag-Relative Sparse Attention In Long Context Training In: Proceedings of the 41st Inter- national Conference on Machine Learning

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 4a43fa87-0313-4e3c-bc61-5b1fe083beee · outbound

This paper cites Advances in neural information pro- cessing systems30(2017).

Lag-Relative Sparse Attention In Long Context Training Advances in neural information pro- cessing systems30(2017)

Reference 30

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Observation 2d0b8531-07fd-4d2b-9e1f-5acb8da24bb2 · outbound

This paper cites Neurocomputing 639, 130193 (2025).

Lag-Relative Sparse Attention In Long Context Training Neurocomputing 639, 130193 (2025)

Reference 31

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 425cc9a5-9881-41dc-83e2-a397465c72f0 · outbound

This paper cites SVD-LLM: Truncation-aware Singular Value Decomposition for Large Language Model Compression.

Lag-Relative Sparse Attention In Long Context Training SVD-LLM: Truncation-aware Singular Value Decomposition for Large Language Model Compression

Reference 32

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Observation d1134c5e-e1ca-476f-8ab7-1c9149894f03 · outbound

This paper cites Beyond the Limits: A Survey of Techniques to Extend the Context Length in Large Language Models.

Lag-Relative Sparse Attention In Long Context Training Beyond the Limits: A Survey of Techniques to Extend the Context Length in Large Language Models

Reference 33

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Observation c9863385-8ff4-48f3-abdb-17f30cb769db · outbound

This paper cites Efficient Streaming Language Models with Attention Sinks.

Lag-Relative Sparse Attention In Long Context Training Efficient Streaming Language Models with Attention Sinks

Reference 34

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Observation 7d858341-c554-4867-83dc-9affe32268aa · outbound

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

Lag-Relative Sparse Attention In Long Context Training Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention

Reference 35

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Observation 56f79d8c-4bff-4689-b515-d04403ebe265 · outbound

This paper cites Advances in neural information processing systems33, 17283–17297 (2020).

Lag-Relative Sparse Attention In Long Context Training Advances in neural information processing systems33, 17283–17297 (2020)

Reference 36

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Observation f075099b-2eb5-4225-88f1-5d9e0ed8b034 · outbound

This paper cites AnchorAttention: Difference-Aware Sparse Attention with Stripe Granularity.

Lag-Relative Sparse Attention In Long Context Training AnchorAttention: Difference-Aware Sparse Attention with Stripe Granularity

Reference 37

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T04:10:49.923424Z digest=sha256:329f4aa3dd0be10333ae5e258612f865d85e3e0fe7715f0f0afa921f0eab87aa

Observation 2d1b7631-13f6-487b-b674-6251e5079563 · outbound

This paper cites Advances in Neural Information Processing Systems36, 34661–34710 (2023).

Lag-Relative Sparse Attention In Long Context Training Advances in Neural Information Processing Systems36, 34661–34710 (2023)

Reference 38

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source=pdf_text observed=2026-08-07T04:10:50.032662Z digest=sha256:b7ec93469c503b82714ff68699dc09b4229e4121936aa06a5e55c38049dd776c

Pith citing papers

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