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Paper Citation Record · LEDGER

FlexiSAGA: A Flexible Systolic Array GEMM Accelerator for Sparse and Dense Processing

As of 7 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2506.01566.

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

pith.paper-citation-record.v1
2506.01566 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:44:12.092976Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

19 of 19 outbound references displayed

  • verified exact0
  • verified fuzzy17
  • unresolved2
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 253306fb-7814-4e05-aab3-f4587bda6d40 · outbound

This paper cites an unresolved cited work.

FlexiSAGA: A Flexible Systolic Array GEMM Accelerator for Sparse and Dense Processing Unresolved cited work

Reference 1

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation e0297eff-af56-4624-91d4-82ba9ab2f6c9 · outbound

This paper cites et al.: UltraTrail: A Configurable Ultralow-Power TC-ResNet AI Ac- celerator for Efficient Keyword Spotting.

FlexiSAGA: A Flexible Systolic Array GEMM Accelerator for Sparse and Dense Processing et al.: UltraTrail: A Configurable Ultralow-Power TC-ResNet AI Ac- celerator for Efficient Keyword Spotting

Reference 2

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 919b58a6-139c-4635-8297-88a36755f797 · outbound

This paper cites In: Tenth International Workshop on Frontiers in Handwriting Recognition.

FlexiSAGA: A Flexible Systolic Array GEMM Accelerator for Sparse and Dense Processing In: Tenth International Workshop on Frontiers in Handwriting Recognition

Reference 3

Resolution
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Source-reported events for the cited work

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Observation 0f38f4c0-f2cf-4e82-8325-a20c964d7134 · outbound

This paper cites et al.: Eyeriss: An Energy-Efficient Reconfigurable Accelerator for Deep Convolutional Neural Networks.

FlexiSAGA: A Flexible Systolic Array GEMM Accelerator for Sparse and Dense Processing et al.: Eyeriss: An Energy-Efficient Reconfigurable Accelerator for Deep Convolutional Neural Networks

Reference 4

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 06526337-9e89-4a52-b36d-919bf9eaf639 · outbound

This paper cites IEEE Transactions on Pattern Analysis and Machine Intelligence46(12), 10558–10578 (2024).

FlexiSAGA: A Flexible Systolic Array GEMM Accelerator for Sparse and Dense Processing IEEE Transactions on Pattern Analysis and Machine Intelligence46(12), 10558–10578 (2024)

Reference 5

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 9594eef0-ecd3-4c97-b3e2-adfb3b15eb72 · outbound

This paper cites In: 20th International Symposium on Qual- ity Electronic Design (ISQED).

FlexiSAGA: A Flexible Systolic Array GEMM Accelerator for Sparse and Dense Processing In: 20th International Symposium on Qual- ity Electronic Design (ISQED)

Reference 6

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation c9790160-87f9-439b-8ec2-de390c456750 · outbound

This paper cites et al.: Gemmini: Enabling Systematic Deep-Learning Architecture Eval- uation via Full-Stack Integration.

FlexiSAGA: A Flexible Systolic Array GEMM Accelerator for Sparse and Dense Processing et al.: Gemmini: Enabling Systematic Deep-Learning Architecture Eval- uation via Full-Stack Integration

Reference 7

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 9167cbf1-a737-4c3e-a783-d755802467ff · outbound

This paper cites et al.: SparTen: A Sparse Tensor Accelerator for Convolutional Neural Networks.

FlexiSAGA: A Flexible Systolic Array GEMM Accelerator for Sparse and Dense Processing et al.: SparTen: A Sparse Tensor Accelerator for Convolutional Neural Networks

Reference 8

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 4da46066-1992-4a04-b872-8939f5d4c31e · outbound

This paper cites et al.: Deep Residual Learning for Image Recognition (2015).

FlexiSAGA: A Flexible Systolic Array GEMM Accelerator for Sparse and Dense Processing et al.: Deep Residual Learning for Image Recognition (2015)

Reference 9

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation b15e6606-d929-4972-92db-90a44049fc3f · outbound

This paper cites et al.: How Well Do Sparse ImageNet Models Transfer? In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

FlexiSAGA: A Flexible Systolic Array GEMM Accelerator for Sparse and Dense Processing et al.: How Well Do Sparse ImageNet Models Transfer? In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Reference 10

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 654751ce-080b-4047-85f9-fa7e0645f81d · outbound

This paper cites Communications of the ACM60(6), 84–90 (May 2017).

FlexiSAGA: A Flexible Systolic Array GEMM Accelerator for Sparse and Dense Processing Communications of the ACM60(6), 84–90 (May 2017)

Reference 11

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:44:11.959770Z digest=sha256:fc5b9550af03925753d6ba4a1663b354df36fd80847bc80620ce6f44aeb08980

Observation b4aa9808-a0ba-457d-aa55-c15d42a21a76 · outbound

This paper cites et al.: Sparse Fine-tuning for Inference Acceleration of Large Language Models (2023).

FlexiSAGA: A Flexible Systolic Array GEMM Accelerator for Sparse and Dense Processing et al.: Sparse Fine-tuning for Inference Acceleration of Large Language Models (2023)

Reference 12

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation b6bbab36-1c97-4db9-8c72-a0365bf8a1d0 · outbound

This paper cites et al.: Accelerating Sparse Deep Neural Networks (2021).

FlexiSAGA: A Flexible Systolic Array GEMM Accelerator for Sparse and Dense Processing et al.: Accelerating Sparse Deep Neural Networks (2021)

Reference 13

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T11:44:11.998901Z digest=sha256:0d4d7b4855dcb64c5f25d4acd0e442eab402e82d9f3cf33daff3f567ac46b974

Observation b9c07119-9d2a-4ed5-9a17-51fef8f583c5 · outbound

This paper cites et al.: SCNN: An Accelerator for Compressed-sparse Convolutional Neural Networks.

FlexiSAGA: A Flexible Systolic Array GEMM Accelerator for Sparse and Dense Processing et al.: SCNN: An Accelerator for Compressed-sparse Convolutional Neural Networks

Reference 14

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 53c605ca-6838-43df-a1e0-72378f9dc8fe · outbound

This paper cites et al.: PyTorch: An Imperative Style, High-Performance Deep Learning Library.

FlexiSAGA: A Flexible Systolic Array GEMM Accelerator for Sparse and Dense Processing et al.: PyTorch: An Imperative Style, High-Performance Deep Learning Library

Reference 15

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 4d5c6100-e1a6-4ce5-b2ed-b583f5d1ea7e · outbound

This paper cites an unresolved cited work.

FlexiSAGA: A Flexible Systolic Array GEMM Accelerator for Sparse and Dense Processing Unresolved cited work

Reference 16

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 44ce1e6a-2bbc-44fb-9532-701222bad20c · outbound

This paper cites ACMTransactionsonArchitectureandCodeOptimization19(3),1–26(May2022).

FlexiSAGA: A Flexible Systolic Array GEMM Accelerator for Sparse and Dense Processing ACMTransactionsonArchitectureandCodeOptimization19(3),1–26(May2022)

Reference 17

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 50705c9e-b25f-411e-9111-f4cc2777f995 · outbound

This paper cites et al.: Going Deeper with Convolutions.

FlexiSAGA: A Flexible Systolic Array GEMM Accelerator for Sparse and Dense Processing et al.: Going Deeper with Convolutions

Reference 18

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation cad29a81-d81a-4cd0-a955-996a2d605f8a · outbound

This paper cites et al.: Learning Structured Sparsity in Deep Neural Networks.

FlexiSAGA: A Flexible Systolic Array GEMM Accelerator for Sparse and Dense Processing et al.: Learning Structured Sparsity in Deep Neural Networks

Reference 19

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Pith citing papers

No inbound Pith citation observations are available.