Paper Citation Record · LEDGER

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign

As of 10 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2501.18953.

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

pith.paper-citation-record.v1
2501.18953 v2

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T21:57:13.675007Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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 fuzzy20
unresolved14
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malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation dd328713-eee6-457f-8390-3e5972f57adc · outbound

This paper cites FlexNN: A Dataflow-aware Flexible Deep Learning Accelerator for Energy-Efficient Edge Devices.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign FlexNN: A Dataflow-aware Flexible Deep Learning Accelerator for Energy-Efficient Edge Devices

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-09T21:57:13.484732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0dd107dd-ec48-4909-94d4-27d7e36b4071 · outbound

This paper cites Going deeper with convolutions,.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign Going deeper with convolutions,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:57:14.496215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2bcabf49-3a9f-4ecc-9881-b9d94d69b5f6 · outbound

This paper cites SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-09T21:57:13.495517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b299349-2fef-4291-8c7f-bdbd3077a797 · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-09T21:57:13.501237Z

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Unavailable: canonical work link unavailable.

Observation b396912e-7a3d-4a69-bf50-25f1cf43abac · outbound

This paper cites EfficientNetV2: Smaller Models and Faster Training.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign EfficientNetV2: Smaller Models and Faster Training

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-09T21:57:13.506533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a20139a-6ad0-4395-936f-cd02737bfee1 · outbound

This paper cites Shufflenet: An extremely efficient convolutional neural network for mobile devices,.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign Shufflenet: An extremely efficient convolutional neural network for mobile devices,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-09T21:57:13.511881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99eb3ceb-3337-4c0c-b389-1a8aedb07746 · outbound

This paper cites Xception: Deep learning with depthwise separable convolu- tions,.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign Xception: Deep learning with depthwise separable convolu- tions,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-09T21:57:13.517612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d970deb-bd8c-4791-9039-b2c4765ef508 · outbound

This paper cites Neural architecture search with reinforcement learning,.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign Neural architecture search with reinforcement learning,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:57:14.431192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c53a4148-5265-4da3-95c5-6037fdbd2dbe · outbound

This paper cites ProxylessNAS: Direct neural architecture search on target task and hardware,.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign ProxylessNAS: Direct neural architecture search on target task and hardware,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:57:14.382626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 616c33a3-414f-4245-95d6-e4b7397e3c2c · outbound

This paper cites MnasNet: Platform-aware neural architecture search for mobile,.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign MnasNet: Platform-aware neural architecture search for mobile,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:57:14.356784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8d1032ff-d9d2-4ad0-bb6c-5a11554d3b7a · outbound

This paper cites DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-09T21:57:13.543297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94d24f96-326f-4173-a5f0-5134aa0ebbe6 · outbound

This paper cites Binarized neural networks,.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign Binarized neural networks,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:57:14.330911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 14c23fe6-8865-4c64-8965-769223b690dd · outbound

This paper cites FINN: A framework for fast, scalable binarized neural network inference,.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign FINN: A framework for fast, scalable binarized neural network inference,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:57:14.307678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation de65f252-ad0a-4136-86aa-1102d93c5c57 · outbound

This paper cites Highly efficient 8-bit low precision inference of convolutional neural networks with IntelCaffe,.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign Highly efficient 8-bit low precision inference of convolutional neural networks with IntelCaffe,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:57:14.281672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 687e22c4-b3f1-4802-b0d9-6f33d152133f · outbound

This paper cites Trained quantization thresholds for accurate and efficient fixed-point inference of deep neural networks,.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign Trained quantization thresholds for accurate and efficient fixed-point inference of deep neural networks,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:57:14.259889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 99315b25-d468-4e1a-a40b-5f0edb9decbb · outbound

This paper cites XOR-Net: An efficient computation pipeline for binary neural network inference on edge devices,.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign XOR-Net: An efficient computation pipeline for binary neural network inference on edge devices,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:57:14.238399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a1064a96-8d65-4d42-81ea-8885b161df39 · outbound

This paper cites Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-09T21:57:13.576311Z

Source-reported events for the cited work

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Observation 7dd8a13b-5c57-4499-8604-169f6dcbefec · outbound

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

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign Learning both weights and connections for efficient neural network,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-09T21:57:13.581923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a120ec7c-2357-4abb-90ff-70f42c771708 · outbound

This paper cites Pruning Filters for Efficient ConvNets.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign Pruning Filters for Efficient ConvNets

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-09T21:57:13.590533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2df30c03-476f-44bb-b276-aaeed1b384c7 · outbound

This paper cites Block-Sparse Recurrent Neural Networks.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign Block-Sparse Recurrent Neural Networks

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-09T21:57:13.596161Z

Source-reported events for the cited work

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Observation 1d969325-7e88-42c8-86d4-f9246e1d54f1 · outbound

This paper cites CondenseNet: An Efficient DenseNet using Learned Group Convolutions.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign CondenseNet: An Efficient DenseNet using Learned Group Convolutions

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9dbad7b4-98c2-4fac-9311-f7e3c29f698a · outbound

This paper cites Accelerating Sparse Deep Neural Networks.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign Accelerating Sparse Deep Neural Networks

Reference 22

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cd8c37a-c20a-45e0-8843-11f7d050315b · outbound

This paper cites The rising costs of training frontier AI models.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign The rising costs of training frontier AI models

Reference 23

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a482670-dc83-43eb-aef6-1aa994da0be4 · outbound

This paper cites XVDPU: A high performance cnn accelerator on versal platform powered by ai engine,.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign XVDPU: A high performance cnn accelerator on versal platform powered by ai engine,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:57:14.201764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4aecdd22-9567-420b-8a6e-122a24aa1f31 · outbound

This paper cites Nvidia hopper h100 gpu: Scaling performance,.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign Nvidia hopper h100 gpu: Scaling performance,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-09T21:57:13.624492Z

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Observation ece1ef8c-5f37-427b-9d47-3c6f008c08c8 · outbound

This paper cites ThiNet: A filter level pruning method for deep neural network compression,.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign ThiNet: A filter level pruning method for deep neural network compression,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:57:14.157621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1f278d14-2c8c-4c99-a975-ac6d56c17081 · outbound

This paper cites Reconciling sparse and structured pruning: A scientific study of block sparsity,.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign Reconciling sparse and structured pruning: A scientific study of block sparsity,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:57:14.137763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 42f366af-534b-485c-94ef-71d46f90689a · outbound

This paper cites Accelerating sparsity in the NVIDIA Ampere architecture,.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign Accelerating sparsity in the NVIDIA Ampere architecture,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:57:14.116127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 818b2671-e640-4497-b805-684f2a898a02 · outbound

This paper cites Deep neural network compression by in-parallel pruning-quantization,.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign Deep neural network compression by in-parallel pruning-quantization,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:57:14.098944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9dc40482-5b30-4376-963c-0cf20d17abd9 · outbound

This paper cites LogNet: Energy-efficient neural networks using logarithmic computation,.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign LogNet: Energy-efficient neural networks using logarithmic computation,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:57:14.078794Z

Source-reported events for the cited work

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Observation 4e401a2a-cf60-4d8c-ab95-d695c7c4433a · outbound

This paper cites Deepshift: Towards multiplication-less neural networks,.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign Deepshift: Towards multiplication-less neural networks,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:57:14.060859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7176dbd4-8196-4c83-b0d1-fce4752d798e · outbound

This paper cites DRQ: Dynamic region-based quantization for deep neural network acceleration,.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign DRQ: Dynamic region-based quantization for deep neural network acceleration,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:57:14.043016Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 36e7b1bf-b71f-4bd4-a197-8b9b0c3c41e6 · outbound

This paper cites HAQ: Hardware-aware automated quantization with mixed precision,.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign HAQ: Hardware-aware automated quantization with mixed precision,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:57:14.016142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 480dfdbe-3357-470e-add0-7e9797dea23e · outbound

This paper cites Chisel: constructing hardware in a scala embedded language,.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign Chisel: constructing hardware in a scala embedded language,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:57:13.996462Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d97f63a5-844a-4e8d-91f5-067b764936ab · outbound

This paper cites Available: https://openreview.net/forum?id=r1Ue8Hcxg.

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign Available: https://openreview.net/forum?id=r1Ue8Hcxg

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T21:57:14.405932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

No inbound Pith citation observations are available.