Paper Citation Record · LEDGER

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge

As of 16 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:1908.02386.

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

pith.paper-citation-record.v1
1908.02386 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T14:49:54.249617Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

47 of 47 outbound references displayed

verified exact1
verified fuzzy28
unresolved17
parse uncertain0
malformed identifier1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4e727e4f-d3d5-46d1-a5fc-c87ecf9a8c8e · outbound

This paper cites Edge intelligence: On-demand deep learning model co-inference with device-edge synergy,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Edge intelligence: On-demand deep learning model co-inference with device-edge synergy,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:55.061759Z

Source-reported events for the cited work

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Observation 3c09f31f-2a4d-4b86-bbea-159ea064c32c · outbound

This paper cites Edge computing: Vision and challenges,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Edge computing: Vision and challenges,

Reference 2

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Source-reported events for the cited work

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Observation 5ba41f2b-30f9-486a-ac23-ea22034f07ce · outbound

This paper cites The emergence of edge computing,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge The emergence of edge computing,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-14T14:49:54.048772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66ab4baf-218b-4361-b231-b67adb197c6c · outbound

This paper cites Imagenet classiﬁcation with deep convolutional neural networks,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Imagenet classiﬁcation with deep convolutional neural networks,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:55.032175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation bb929f68-c55b-4d72-ba4c-8fdb2d7cc25c · outbound

This paper cites 1.1 computing’s energy problem (and what we can do about it),.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge 1.1 computing’s energy problem (and what we can do about it),

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-14T14:49:54.058146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2addd4b-cba4-479a-a0e9-75589c66734d · outbound

This paper cites Scaling for edge inference of deep neural networks,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Scaling for edge inference of deep neural networks,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:55.006570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 4b7545ae-9d9a-4d5f-9ffc-c317d9259222 · outbound

This paper cites Ma- chine learning at facebook: Understanding inference at the edge,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Ma- chine learning at facebook: Understanding inference at the edge,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:54.991937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3dd676a9-2774-4035-a526-b6c174b1f3bf · outbound

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

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cb46330-a342-4dbc-ad28-e051fe054986 · outbound

This paper cites Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution

Reference 9

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Source-reported events for the cited work

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Observation 89eede53-928f-4ba1-a739-1bbd4c5c9309 · outbound

This paper cites MEC: Memory-efﬁcient convolution for deep neural network,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge MEC: Memory-efﬁcient convolution for deep neural network,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:54.977563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d13d4497-e503-42b5-b5a9-95ff69b158f1 · outbound

This paper cites Sbnet: Sparse blocks network for fast inference,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Sbnet: Sparse blocks network for fast inference,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:54.963877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation f375c423-57bc-4338-b571-b6d7db888bd9 · outbound

This paper cites Revisiting the Importance of Individual Units in CNNs via Ablation.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Revisiting the Importance of Individual Units in CNNs via Ablation

Reference 12

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Source-reported events for the cited work

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Observation 84a48900-bd3a-43df-bb31-392716ea33ef · outbound

This paper cites Quantization and training of neural networks for efﬁcient integer-arithmetic-only inference,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Quantization and training of neural networks for efﬁcient integer-arithmetic-only inference,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:54.950437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation dc3bac1f-9951-4747-ac70-1a15019ad321 · outbound

This paper cites Training deep neural networks with 8-bit ﬂoating point numbers,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Training deep neural networks with 8-bit ﬂoating point numbers,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:54.937366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 25fcb10f-b037-4f1e-92a0-c3ccf84dfb86 · outbound

This paper cites Understanding the impact of precision quantization on the accuracy and energy of neural networks,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Understanding the impact of precision quantization on the accuracy and energy of neural networks,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-14T14:49:54.104045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d3d676b-1a58-4a55-a4f2-f0468abb1a58 · outbound

This paper cites Ristretto: A frame- work for empirical study of resource-efﬁcient inference in convolutional neural networks,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Ristretto: A frame- work for empirical study of resource-efﬁcient inference in convolutional neural networks,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:54.924637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 156d393b-f1bb-4d89-9044-bf93146146e0 · outbound

This paper cites A Survey on Methods and Theories of Quantized Neural Networks.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge A Survey on Methods and Theories of Quantized Neural Networks

Reference 17

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Source-reported events for the cited work

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Observation 7a618b9e-ca4b-4556-982c-944e91c2a035 · outbound

This paper cites Quantizing deep convolutional networks for efficient inference: A whitepaper.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Quantizing deep convolutional networks for efficient inference: A whitepaper

Reference 18

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Source-reported events for the cited work

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Observation 61bc8c5d-951a-46fd-8392-2a3b075ef715 · outbound

This paper cites Deep learning infer- ence on embedded devices: Fixed-point vs posit,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Deep learning infer- ence on embedded devices: Fixed-point vs posit,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:54.911564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation bb65a335-21ad-4daa-baad-347e103f12f4 · outbound

This paper cites Deep positron: A deep neural network using the posit number system,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Deep positron: A deep neural network using the posit number system,

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7ace154-80e6-4c45-a40d-c2f25fe34ad5 · outbound

This paper cites Performance-efﬁciency trade-off of low-precision numerical formats in deep neural networks,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Performance-efﬁciency trade-off of low-precision numerical formats in deep neural networks,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:54.899249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e4690574-8fc1-4aad-921a-e0944fee8ed2 · outbound

This paper cites Rethinking floating point for deep learning.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Rethinking floating point for deep learning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-14T14:49:54.134149Z

Source-reported events for the cited work

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Observation 5afa8121-1272-45e7-8ac2-afd4f7476b4c · outbound

This paper cites Gradient-based learning applied to document recognition,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Gradient-based learning applied to document recognition,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-14T14:49:54.140178Z

Source-reported events for the cited work

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Observation c73b44ca-eaad-43af-8cef-7ace5fee4317 · outbound

This paper cites Goodfellow, Y.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Goodfellow, Y

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-14T14:49:54.145518Z

Source-reported events for the cited work

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Observation a07d99f2-54a8-4a5b-b2f3-820228fc1188 · outbound

This paper cites Beating ﬂoating point at its own game: Posit arithmetic,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Beating ﬂoating point at its own game: Posit arithmetic,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:54.873092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 5a7d1746-19af-4c9b-a714-e2f38e0af120 · outbound

This paper cites Unums 2.0: An interview with John L. Gustafson,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Unums 2.0: An interview with John L. Gustafson,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:54.860479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d5e0cab4-d034-4fb1-8b90-6c93486a000c · outbound

This paper cites VLSI implementation of a neural network model,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge VLSI implementation of a neural network model,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:54.847970Z

Source-reported events for the cited work

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Observation 67580cc0-74cf-4d62-9717-c2da992470f9 · outbound

This paper cites An arti- ﬁcial neural network accelerator using general purpose 24 bits ﬂoating point digital signal processors,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge An arti- ﬁcial neural network accelerator using general purpose 24 bits ﬂoating point digital signal processors,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:54.835472Z

Source-reported events for the cited work

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Observation 67f28091-e7cb-4842-876b-c8ddd17446c4 · outbound

This paper cites A VLSI architecture for high-performance, low- cost, on-chip learning,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge A VLSI architecture for high-performance, low- cost, on-chip learning,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:54.823496Z

Source-reported events for the cited work

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Observation 3306648f-79a2-4d6b-ad37-d7a53fbdcbf2 · outbound

This paper cites Experimental determination of precision requirements for back-propagation training of artiﬁcial neural networks,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Experimental determination of precision requirements for back-propagation training of artiﬁcial neural networks,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:54.808688Z

Source-reported events for the cited work

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Observation d7d640f7-e740-4e93-b4f7-e33a42fc6509 · outbound

This paper cites Training with noise is equivalent to tikhonov regular- ization,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Training with noise is equivalent to tikhonov regular- ization,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:54.796656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 38e11f2b-56a5-46d4-a971-f72b6469dd7b · outbound

This paper cites Deep learning with limited numerical precision,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Deep learning with limited numerical precision,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:54.781936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 6e8f3768-66e4-4478-88f6-9e2bc555dc80 · outbound

This paper cites Mixed precision training,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Mixed precision training,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:54.767778Z

Source-reported events for the cited work

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Observation 135c4ef2-eeef-4d70-b0d1-e6ccc08e26e0 · outbound

This paper cites Flexpoint: An adaptive numerical format for efﬁcient training of deep neural networks,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Flexpoint: An adaptive numerical format for efﬁcient training of deep neural networks,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:54.754219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 946b48f1-32d0-4794-9e0c-ace984d24afd · outbound

This paper cites Mixed Precision Training With 8-bit Floating Point.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Mixed Precision Training With 8-bit Floating Point

Reference 36

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Observation 5e99ed80-fe97-4af9-bef3-251a335e0a18 · outbound

This paper cites A Study of BFLOAT16 for Deep Learning Training.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge A Study of BFLOAT16 for Deep Learning Training

Reference 37

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Source-reported events for the cited work

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Observation 92596411-8b78-416d-af2a-411198b0b57c · outbound

This paper cites Serving DNNs in real time at datacenter scale with Project Brainwave,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Serving DNNs in real time at datacenter scale with Project Brainwave,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:54.740940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation de4e5fdc-2259-409a-9563-e2a6df65ede5 · outbound

This paper cites Rounding errors in algebraic processes,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Rounding errors in algebraic processes,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:54.720252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation a2318a24-ad6e-4d5b-b25d-e4200c34baa5 · outbound

This paper cites Posits: the good, the bad and the ugly,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Posits: the good, the bad and the ugly,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:54.706514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 1a9e84b6-7ec5-4061-9cc4-97ba87bb4d55 · outbound

This paper cites The use of multiple measurements in taxonomic prob- lems,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge The use of multiple measurements in taxonomic prob- lems,

Reference 41

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Source-reported events for the cited work

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Observation dc4466b7-8d10-4d5d-a5b4-91bb95042d7f · outbound

This paper cites Kulisch, Computer arithmetic and validity: theory, implementation, and applications , 1st ed., ser.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Kulisch, Computer arithmetic and validity: theory, implementation, and applications , 1st ed., ser

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:54.677420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 13a99f98-da73-4aa0-93d2-3ee9aa2b6bbd · outbound

This paper cites Chollet et al., “Keras,” https://github.com/keras-team/keras, 2015.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Chollet et al., “Keras,” https://github.com/keras-team/keras, 2015

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:54.663449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 68c9ad4c-808e-479a-a756-91e950953715 · outbound

This paper cites TensorFlow: Large-scale machine learning on heterogeneous systems,.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge TensorFlow: Large-scale machine learning on heterogeneous systems,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:54.649654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation bd44aa26-fdae-4c80-8fb9-bffc5d35a053 · outbound

This paper cites Training deep neural networks with low precision multiplications.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Training deep neural networks with low precision multiplications

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-14T14:49:54.249617Z

Source-reported events for the cited work

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Observation 7bd783db-5b98-4edc-826f-2c96af1402ca · outbound

This paper cites Available: https://doi.org/10.1109/IJCNN.1990.137621.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Available: https://doi.org/10.1109/IJCNN.1990.137621

Reference 544

Resolution: unresolved; no resolver link, observed 2026-08-14T14:49:54.176393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c524ede-5c1d-4b84-86ca-01ce53e4fbf0 · outbound

This paper cites Available: https://doi.org/10.1109/2.30.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Available: https://doi.org/10.1109/2.30

Reference 1988

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Observation 6bd1a184-8394-4f9f-b4ba-238926161147 · outbound

This paper cites Available: https://www.tensorﬂow.org/.

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge Available: https://www.tensorﬂow.org/

Reference 2015

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:49:54.635194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Pith citing papers

No inbound Pith citation observations are available.