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Paper Citation Record · LEDGER

Efficient Column-Wise N:M Pruning on RISC-V CPU

As of 18 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2507.17301.

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

pith.paper-citation-record.v1
2507.17301 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:55:28.447293Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

44 of 44 outbound references displayed

  • verified exact7
  • verified fuzzy23
  • unresolved14
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2c59e865-bacd-4476-8524-6ad07971dc04 · outbound

This paper cites Low-memory GEMM-based convolution algorithms for deep neural networks.

Efficient Column-Wise N:M Pruning on RISC-V CPU Low-memory GEMM-based convolution algorithms for deep neural networks

Reference 1

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Observation 7b4bc148-c9d0-411b-abe3-99cc4ac70d14 · outbound

This paper cites Structured sparsity in the nvidia ampere architecture and its applica- tions.

Efficient Column-Wise N:M Pruning on RISC-V CPU Structured sparsity in the nvidia ampere architecture and its applica- tions

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 3ee1ac38-5aff-4d23-8c93-c5580fb91aad · outbound

This paper cites Progressive Gradient Flow for Robust N:M Sparsity Training in Transformers.

Efficient Column-Wise N:M Pruning on RISC-V CPU Progressive Gradient Flow for Robust N:M Sparsity Training in Transformers

Reference 3

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Observation 9422e8e1-fa39-4b19-8783-6667a8def957 · outbound

This paper cites Banana Pi BPI-F3: RISC-V Single Board Computer.

Efficient Column-Wise N:M Pruning on RISC-V CPU Banana Pi BPI-F3: RISC-V Single Board Computer

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T14:55:28.339441Z digest=sha256:6776e7436738f263142015f1d3521760e362dee46cd5ad71a293b7f57aff392a

Observation a61794fb-f7b6-4fe3-84ea-4fcbd92f7e75 · outbound

This paper cites Gradient and magnitude-based pruning for sparse deep neural networks.

Efficient Column-Wise N:M Pruning on RISC-V CPU Gradient and magnitude-based pruning for sparse deep neural networks

Reference 5

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doi, observed 2026-08-06T14:55:28.503295Z

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Observation e2e94b0c-336d-4527-87d6-01d0e5526349 · outbound

This paper cites Fraguela, and Torsten Hoefler.

Efficient Column-Wise N:M Pruning on RISC-V CPU Fraguela, and Torsten Hoefler

Reference 6

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Observation 61b34e69-f3db-43fe-8131-00bfdfb87630 · outbound

This paper cites Accelerating gnns on gpu sparse tensor cores through n:m sparsity-oriented graph reordering.

Efficient Column-Wise N:M Pruning on RISC-V CPU Accelerating gnns on gpu sparse tensor cores through n:m sparsity-oriented graph reordering

Reference 7

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source=pdf_text observed=2026-08-06T14:55:28.348516Z digest=sha256:ef7362b36d7445186b44f6053fd93f1bf3b8de8b1f3412c841c22fd1fa2ad068

Observation 6fcf8dbf-7f4e-4ea5-b924-7f6caa555499 · outbound

This paper cites Minimum variance unbiased n :m sparsity for the neural gradients.

Efficient Column-Wise N:M Pruning on RISC-V CPU Minimum variance unbiased n :m sparsity for the neural gradients

Reference 8

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Observation cf7084d5-7d02-449b-b004-3c10ce6d2b31 · outbound

This paper cites Xne: an ultra-low energy convolutional neural network accelerator for embedded systems.

Efficient Column-Wise N:M Pruning on RISC-V CPU Xne: an ultra-low energy convolutional neural network accelerator for embedded systems

Reference 9

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Source-reported events for the cited work

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Observation bf7dc61d-e265-497b-9e92-94ee822e50d6 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Efficient Column-Wise N:M Pruning on RISC-V CPU Imagenet: A large-scale hierarchical image database

Reference 10

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Observation 2dfd59ac-3a13-481b-b170-b5df1ba0e0c7 · outbound

This paper cites Learning to Prune Deep Neural Networks via Layer-wise Optimal Brain Surgeon.

Efficient Column-Wise N:M Pruning on RISC-V CPU Learning to Prune Deep Neural Networks via Layer-wise Optimal Brain Surgeon

Reference 11

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Observation 488de650-a313-423d-a2ad-53c71e553fe3 · outbound

This paper cites The Indirect Convolution Algorithm.

Efficient Column-Wise N:M Pruning on RISC-V CPU The Indirect Convolution Algorithm

Reference 12

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T14:55:28.362383Z digest=sha256:96681f96e0f7347aa3489abf411201c52f1f9cfba5cecb39f2c35b2f1b14e58e

Observation 456bd5da-40c2-4daa-b64b-43cec9a296b5 · outbound

This paper cites Fast sparse convnets.

Efficient Column-Wise N:M Pruning on RISC-V CPU Fast sparse convnets

Reference 13

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Observation 5f78f59d-9e08-44ed-8c83-c36842947d22 · outbound

This paper cites Gap-8: A risc-v soc for ai at the edge of the iot.

Efficient Column-Wise N:M Pruning on RISC-V CPU Gap-8: A risc-v soc for ai at the edge of the iot

Reference 14

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Observation 0e0005c1-dc2b-4da3-9ff5-7f4654567325 · outbound

This paper cites The State of Sparsity in Deep Neural Networks.

Efficient Column-Wise N:M Pruning on RISC-V CPU The State of Sparsity in Deep Neural Networks

Reference 15

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Observation 7a7e4785-d93a-4592-bc61-9e9d01814760 · outbound

This paper cites Xnnpack: Efficient inference library for neural network operators, 2024.

Efficient Column-Wise N:M Pruning on RISC-V CPU Xnnpack: Efficient inference library for neural network operators, 2024

Reference 16

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Observation c8b3d39f-6984-4089-a6b9-0f0f9bdd4c5d · outbound

This paper cites Dynamic network surgery for efficient DNNs.

Efficient Column-Wise N:M Pruning on RISC-V CPU Dynamic network surgery for efficient DNNs

Reference 17

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Observation 4c8f5425-da8d-4729-bb00-d27c214353c4 · outbound

This paper cites Learning both weights and connections for efficient neural network.

Efficient Column-Wise N:M Pruning on RISC-V CPU Learning both weights and connections for efficient neural network

Reference 18

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Observation 87699cd0-2a83-4c86-a3db-17688c58e112 · outbound

This paper cites Deep residual learning for image recognition.

Efficient Column-Wise N:M Pruning on RISC-V CPU Deep residual learning for image recognition

Reference 19

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Observation 49c37249-8162-4fe6-b447-d3d5c6e6ff55 · outbound

This paper cites Soft filter pruning for accelerating deep convolutional neural networks.

Efficient Column-Wise N:M Pruning on RISC-V CPU Soft filter pruning for accelerating deep convolutional neural networks

Reference 20

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Observation e47648b6-9932-4c27-9774-c4a213b024e3 · outbound

This paper cites Channel pruning for accelerating very deep neural networks.

Efficient Column-Wise N:M Pruning on RISC-V CPU Channel pruning for accelerating very deep neural networks

Reference 21

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Observation 8f272b94-8175-4ca0-bce1-4460d413db5b · outbound

This paper cites Weinberger.

Efficient Column-Wise N:M Pruning on RISC-V CPU Weinberger

Reference 22

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Observation fa915377-eb78-443f-aec8-7fd0c76e2513 · outbound

This paper cites ELSA: Exploiting Layer-wise N:M Sparsity for Vision Transformer Acceleration.

Efficient Column-Wise N:M Pruning on RISC-V CPU ELSA: Exploiting Layer-wise N:M Sparsity for Vision Transformer Acceleration

Reference 23

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local_arxiv, observed 2026-08-06T14:55:28.602113Z

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source=pdf_text observed=2026-08-06T14:55:28.390496Z digest=sha256:149d6c30adad00481d4b61b78987a15f970c4c8b0529830e08a01a7c8bd5cd47

Observation 93b8a0eb-4d28-48bd-a27a-49e5b05ce483 · outbound

This paper cites Accelerated sparse neural training: A provable and efficient method to find n:m transposable masks.

Efficient Column-Wise N:M Pruning on RISC-V CPU Accelerated sparse neural training: A provable and efficient method to find n:m transposable masks

Reference 24

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Observation 16c2bbdf-84b0-487a-9093-30c22b11beb3 · outbound

This paper cites Training Recipe for N:M Structured Sparsity with Decaying Pruning Mask.

Efficient Column-Wise N:M Pruning on RISC-V CPU Training Recipe for N:M Structured Sparsity with Decaying Pruning Mask

Reference 25

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Observation 90ef7a9f-58ea-4e29-bbb6-012236756350 · outbound

This paper cites SNIP: Single-shot Network Pruning based on Connection Sensitivity.

Efficient Column-Wise N:M Pruning on RISC-V CPU SNIP: Single-shot Network Pruning based on Connection Sensitivity

Reference 26

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source=pdf_text observed=2026-08-06T14:55:28.399190Z digest=sha256:f47ef9729d6a0d5c527b5c011e1086988b7c9a14b4ec522c0e8d4a7ff1de8bf0

Observation 65691b9f-773b-47f3-be06-367039e07434 · outbound

This paper cites Group fisher pruning for practical network compression.

Efficient Column-Wise N:M Pruning on RISC-V CPU Group fisher pruning for practical network compression

Reference 27

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Observation d859f99b-58ae-44af-a249-8456556c0cbd · outbound

This paper cites STEP: Learning N:M Structured Sparsity Masks from Scratch with Precondition.

Efficient Column-Wise N:M Pruning on RISC-V CPU STEP: Learning N:M Structured Sparsity Masks from Scratch with Precondition

Reference 28

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local_arxiv, observed 2026-08-06T14:55:28.568024Z

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Observation c5ece88a-4562-41c5-9d1f-ab1ab7ca38d4 · outbound

This paper cites an unresolved cited work.

Efficient Column-Wise N:M Pruning on RISC-V CPU Unresolved cited work

Reference 29

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Observation c2625f6e-f11e-4ef1-97ed-a71d03d22b42 · outbound

This paper cites Meta Platforms.

Efficient Column-Wise N:M Pruning on RISC-V CPU Meta Platforms

Reference 30

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T14:55:28.410374Z digest=sha256:d5017e213ab0169a080392b3b14219c47c195dd86941300d9b6ce245da795a9e

Observation f84431eb-ce6b-4e1d-9c1b-72967bdfaa4f · outbound

This paper cites Accelerating Sparse Deep Neural Networks.

Efficient Column-Wise N:M Pruning on RISC-V CPU Accelerating Sparse Deep Neural Networks

Reference 31

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source=pdf_text observed=2026-08-06T14:55:28.412818Z digest=sha256:2560d364bad90ccaf2791e9985e365c6131bd10a5ce5c38bff826e70a78869ff

Observation 05dbcf62-6398-43e7-a0f4-383ab446e6d3 · outbound

This paper cites Pruning Convolutional Neural Networks for Resource Efficient Inference.

Efficient Column-Wise N:M Pruning on RISC-V CPU Pruning Convolutional Neural Networks for Resource Efficient Inference

Reference 32

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source=pdf_text observed=2026-08-06T14:55:28.415507Z digest=sha256:41c84083089fee35266423845c37a311dbdf300d15cefa8a408c2fe1035b164b

Observation 9e95c82e-1a95-48cc-801e-a2b466ca753d · outbound

This paper cites The RISC–V “V” Vector Extension, Version 1.0.

Efficient Column-Wise N:M Pruning on RISC-V CPU The RISC–V “V” Vector Extension, Version 1.0

Reference 33

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raw_fallback, observed 2026-08-06T14:55:28.828639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T14:55:28.418335Z digest=sha256:ee8ec62c7a4487d5b25ebeb1cdad308f83592d6a0f30f7e1970425b14c84ba54

Observation ca6b81ef-fa5f-4974-b414-75e69acd0c61 · outbound

This paper cites Iterative Methods for Sparse Linear Systems.

Efficient Column-Wise N:M Pruning on RISC-V CPU Iterative Methods for Sparse Linear Systems

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T14:55:28.420998Z digest=sha256:017542b47d046bf6d029c6405947a4870fc4031fe041c5d223997c6c2c777a4d

Observation f39601e3-fe33-498f-a8b5-e92a006864ca · outbound

This paper cites Mo- bileNetV2: Inverted residuals and linear bottlenecks.

Efficient Column-Wise N:M Pruning on RISC-V CPU Mo- bileNetV2: Inverted residuals and linear bottlenecks

Reference 35

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raw_fallback, observed 2026-08-06T14:55:28.811178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation c5a30a94-c60f-4b60-877c-edbce84e2ea7 · outbound

This paper cites an unresolved cited work.

Efficient Column-Wise N:M Pruning on RISC-V CPU Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-06T14:55:28.802266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation b1a1732a-5f2c-46c4-b3db-d2ef24dccf5a · outbound

This paper cites Sifive accelerates RISC–V vector integration in xnnpack for optimized ai inference, Aug.

Efficient Column-Wise N:M Pruning on RISC-V CPU Sifive accelerates RISC–V vector integration in xnnpack for optimized ai inference, Aug

Reference 37

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 7bf6d64e-24a0-4236-b6cd-1fc39a96e82c · outbound

This paper cites Dominosearch: Find layer-wise fine-grained n:m sparse schemes from dense neural networks.

Efficient Column-Wise N:M Pruning on RISC-V CPU Dominosearch: Find layer-wise fine-grained n:m sparse schemes from dense neural networks

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:55:28.776596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T14:55:28.433689Z digest=sha256:dacaec89c2f3f259b78d6c6e3e3bf24c0210274ef45f4a52861d4a7a1cdab726

Observation 828e290c-4146-411d-aa1b-b22b4f845db9 · outbound

This paper cites Pruning neural networks without any data by iteratively conserving synaptic flow.

Efficient Column-Wise N:M Pruning on RISC-V CPU Pruning neural networks without any data by iteratively conserving synaptic flow

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T14:55:28.436138Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:55:28.436138Z digest=sha256:2de4bd675623e938f311af4f55acd9b756729f72d0c61edbec3003747bf6a12b

Observation 7f5701d8-282f-47d1-87d7-5473b6fd962d · outbound

This paper cites Optimizing structured-sparse matrix multiplication in risc-v vector proces- sors.

Efficient Column-Wise N:M Pruning on RISC-V CPU Optimizing structured-sparse matrix multiplication in risc-v vector proces- sors

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:55:28.767421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T14:55:28.438853Z digest=sha256:ee11ab52c93fdcdc782f458e99b2c5ecdcde328121a39ec03e44cdf9d27ec0d5

Observation de031a25-1e16-4682-881b-efdf1ad903b5 · outbound

This paper cites Picking Winning Tickets Before Training by Preserving Gradient Flow.

Efficient Column-Wise N:M Pruning on RISC-V CPU Picking Winning Tickets Before Training by Preserving Gradient Flow

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T14:55:28.441400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:55:28.441400Z digest=sha256:8d8c22e088a5d3f6cfe2ec70db27d8ae464a972896b37bc5a4161711622812c8

Observation 6a6063fa-63d9-4afe-b7a1-8ee8e0902e99 · outbound

This paper cites Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch.

Efficient Column-Wise N:M Pruning on RISC-V CPU Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-06T14:55:28.444237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:55:28.444237Z digest=sha256:01201e432fdb8b2ac64eeb4898b27512549583cf5b61081672156eaf9f88d5be

Observation 8618e3a3-7c68-4eef-9aea-767b1f19bddc · outbound

This paper cites FGGP: Fixed-Rate Gradient-First Gradual Pruning.

Efficient Column-Wise N:M Pruning on RISC-V CPU FGGP: Fixed-Rate Gradient-First Gradual Pruning

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-08-06T14:55:28.515276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T14:55:28.447293Z digest=sha256:919d4bd254f8509b41666d5af7bf4a6871d68215d719fa2492a372294b3dc75a

Observation 288a205c-91b2-4b83-9271-4e2e470597fd · outbound

This paper cites Accessed 6 May 2025.

Efficient Column-Wise N:M Pruning on RISC-V CPU Accessed 6 May 2025

Reference 2023

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:55:28.784963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T14:55:28.431264Z digest=sha256:57d7b129e643c5e62198bae20bb81f1744d3cfbe82cae6f2b44806e3734ca204

Pith citing papers

No inbound Pith citation observations are available.