Pith. sign in

Paper Citation Record · LEDGER

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems

As of 16 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2607.08013.

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

pith.paper-citation-record.v1
2607.08013 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-10T13:44:13.951954Z

measured 35 of 35 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

35 of 35 outbound references displayed

  • verified exact7
  • verified fuzzy27
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bda25f6e-fca3-497b-8004-ae59074f13e5 · outbound

This paper cites A survey on deep learning: Algorithms, techniques, and applications,.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems A survey on deep learning: Algorithms, techniques, and applications,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.019731Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:6666156676afd88814863b26b538d8a5b89cdff8f7affe0513f3d3a95dbba5be

Observation 741af6d4-d377-4fc4-9b2e-b91c0facad28 · outbound

This paper cites Do we need more training data?.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Do we need more training data?

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.026709Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:a620d828cc7a322204810352640c4ee580b9e09c910a0a14af282c6fdf7e796e

Observation ecaf4dee-96c3-42fc-becf-94a85604a031 · outbound

This paper cites Federated machine learning: Concept and applications.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Federated machine learning: Concept and applications

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.034412Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:9ef01e3d474995c4f00c5fa335bce9d6c38bc2aca37503d943f9e7a808dc3fdf

Observation 54a89a4c-67fa-413e-b59a-00e8d0d1e374 · outbound

This paper cites High-throughput cnn inference on embedded arm big. little multicore processors,.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems High-throughput cnn inference on embedded arm big. little multicore processors,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.046691Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:017bf88951548aba4956c93736e92c75e988114a31cac535b298375c50a03f17

Observation 84ca631d-19dd-4c74-ab81-cadb7216e607 · outbound

This paper cites Federated learning for privacy- preserving ai,.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Federated learning for privacy- preserving ai,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.012033Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:040924dcb62b6d02b4208aca5eefe3bdf050a26a4106230500652d978e70cb08

Observation 0c6e25e5-c8ca-494d-8a37-6ec7c63299bd · outbound

This paper cites Parameterized knowledge transfer for personalized federated learning,.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Parameterized knowledge transfer for personalized federated learning,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.031174Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:86ba15b53e6407bd1ef1e7666bb32ecaf2cf9117de6ae744fd1eacdd8fff367c

Observation 0cec6c4b-2261-4a8e-8ffa-8d20d31f6a20 · outbound

This paper cites Helios: heterogeneity-aware federated learning with dynamically balanced collaboration,.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Helios: heterogeneity-aware federated learning with dynamically balanced collaboration,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.023794Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:db4c94ca82fb40265fc89fa3329fbfdbe29c97157c4d5da8a0af2728832123ff

Observation b46c15c8-1999-4341-840a-c5b02e2c8f75 · outbound

This paper cites HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients

Reference 8

Resolution
verified exact
local_arxiv, observed 2026-07-10T13:47:05.777225Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:80f615020d8a966efe84b2eba94e1de03e1a379a33e72f361a32ada79db3d72a

Observation 111293dd-bedd-4e71-96de-4b48d9469316 · outbound

This paper cites FedMD: Heterogenous Federated Learning via Model Distillation.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems FedMD: Heterogenous Federated Learning via Model Distillation

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-07-10T13:47:05.782452Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:58601614d48ac4e97eeb5b8fe0b52b25165633c5ac19a8a514a7e0e72b3fe02c

Observation 984fb18a-01cd-49a1-89fe-ce8c7efd5fc4 · outbound

This paper cites Fedproto: Federated prototype learning across heterogeneous clients,.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Fedproto: Federated prototype learning across heterogeneous clients,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.027412Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:cbc2824fdafa672dddac9c8b4bf6763f86c0e6cc883b9388469e2d15b5d9aa4b

Observation f08b8cc2-2f46-4568-a27a-88260fb16c65 · outbound

This paper cites Distributed Learning of Deep Neural Networks using Independent Subnet Training.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Distributed Learning of Deep Neural Networks using Independent Subnet Training

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-07-10T13:47:05.779617Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:a737851fd8baae40e06b212300024e4e3b2c0dca8fad795e5eab826a51de72e0

Observation 0fc79f15-66cd-4c86-a608-667b7b50d52b · outbound

This paper cites Efficientnet: Rethinking model scaling for con- volutional neural networks.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Efficientnet: Rethinking model scaling for con- volutional neural networks

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.045041Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:62fd558d36ee99d49b95a8cf73b00f36d82061859fb4a72cc38908d2a290c2b2

Observation b003d406-15cd-4487-9bc3-2e7ea3676522 · outbound

This paper cites Communication-efficient learning of deep networks from decentralized data.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Communication-efficient learning of deep networks from decentralized data

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.025538Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:db2abd9f6c7e3c242598bc12b806b3fca6624431cef3b75a406a6df7304cc9a8

Observation c6c17d8a-7520-4e1b-bf6c-aa2e36d632ee · outbound

This paper cites Federated learning: Challenges, methods, and future directions.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Federated learning: Challenges, methods, and future directions

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.043378Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:50d3729dae194eacba1e5a5e9675ae5fc58a6a476ca6277e1c5a29272e5b4c7d

Observation 22b89705-5b3f-477d-9fed-d87d8f347599 · outbound

This paper cites Federated Learning with Non-IID Data.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Federated Learning with Non-IID Data

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-07-10T13:47:05.774063Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:660350b6cecd8809ade5eb61dc00838e8ce5a67155ed11dcfa6bcfb614b0cda6

Observation acffdee1-e094-4c9a-8276-68d842aba7f2 · outbound

This paper cites Federated Evaluation of On-device Personalization.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Federated Evaluation of On-device Personalization

Reference 16

Resolution
verified exact
local_arxiv, observed 2026-07-10T13:47:05.787370Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:7e427316a780776adc01782f1e10ef9dd506d7447c98e48e4834f12c431e51f6

Observation cc1c2751-9614-4a78-88df-cff1151488ef · outbound

This paper cites Improving Federated Learning Personalization via Model Agnostic Meta Learning.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Improving Federated Learning Personalization via Model Agnostic Meta Learning

Reference 17

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T13:47:05.778925Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:f81a9aa1caf25e25ea91a50f9bd0e588d01c85b493e819fc643859a4cf1c3cfa

Observation de970537-29ee-43a2-a6e6-05a5bd701826 · outbound

This paper cites Adaptive gradient- based meta-learning methods,.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Adaptive gradient- based meta-learning methods,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.039848Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:313f36cb64adafbce3e6eca5815d1667762a8fd5940be1cf1eba3c8fea8d61d0

Observation 71b71c4f-4da7-49df-a316-2937ddecbc3e · outbound

This paper cites Expanding the Reach of Federated Learning by Reducing Client Resource Requirements.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Expanding the Reach of Federated Learning by Reducing Client Resource Requirements

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-07-10T13:47:05.786737Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:ba89284fcd315e8358d863c7a3a1537d8a40b569a9476386607fcc9a92345e3d

Observation 43c9da61-fff2-40b3-ab56-255e90eaa4db · outbound

This paper cites Hermes: an efficient federated learning framework for heterogeneous mobile clients,.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Hermes: an efficient federated learning framework for heterogeneous mobile clients,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.038177Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:9972fbd65d8e37bf30151691bcefa4724fbd1cd99eedeb8d83344abce9822860

Observation fefda524-793f-4f49-8581-5b62d5416855 · outbound

This paper cites Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-07-10T13:47:05.785104Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:601b003a1c0b83f2d7091ca3affa76cf73f6c3a0cf29b29753140b106bbfa534

Observation 3ea2bfd6-ecca-4cb4-a978-72f8641fe68e · outbound

This paper cites Mobile blockchain-empowered federated learning: Current situation and further prospect,.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Mobile blockchain-empowered federated learning: Current situation and further prospect,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.041676Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:05edd910c7cf99850a61655989235b30c1f17d63ce74b341ff6c9155bb5122a8

Observation 43298aad-1663-455c-92ef-3ccf85637a35 · outbound

This paper cites Netadapt: Platform-aware neural network adaptation for mobile applications,.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Netadapt: Platform-aware neural network adaptation for mobile applications,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:05.999444Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:51dfeedcfc364e1684e7664f335e649c07cf79f433907cff7ba96bc2c2063405

Observation 0b6df196-2b96-4435-949a-f669d42b8eab · outbound

This paper cites Chamnet: Towards efficient network design through platform-aware model adaptation,.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Chamnet: Towards efficient network design through platform-aware model adaptation,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.024714Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:6bcaa227c35a0e91c6eee855dcf3412e3fa862cfc6f7ccaa1559067f24835df1

Observation 98571336-74ee-49be-ad0a-33616d9a43b9 · outbound

This paper cites Squeezenext: Hardware-aware neural network de- sign,.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Squeezenext: Hardware-aware neural network de- sign,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.001201Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:19499f3b9928ff72f1c47d7ca06b0d67e72f59d02cd8b8fb0e4430344d19dd5f

Observation 84f4c8ca-963e-4b77-a9f8-c32821fcc636 · outbound

This paper cites Fbnet: Hardware-aware efficient convnet design via differentiable neural architecture search,.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Fbnet: Hardware-aware efficient convnet design via differentiable neural architecture search,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.010395Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:3934d92872fff77bcfd1812f30a08f60503809b514820914c7117cede96aa937

Observation 521a1ae3-ffaa-4c8d-8c31-7031f989ba4c · outbound

This paper cites Predicting the computational cost of deep learning models,.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Predicting the computational cost of deep learning models,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.015663Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:dea5aa8b91cd7358ef3df13aa266422f63f20a9bcb29cf8e7e24f6e47faabaa9

Observation d0d8dd6f-0d48-4f4a-a4b9-dab4c2ce2072 · outbound

This paper cites Zerobn: Learning compact neural networks for latency- critical edge systems,.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Zerobn: Learning compact neural networks for latency- critical edge systems,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.048438Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:a192de20f9388f38a3c97517689fa3e099d2e7c43243a37b864369e5bd26b24f

Observation 2ceb4752-cbef-4d0a-9ef6-a6feb9511f0c · outbound

This paper cites Theory of the backpropagation neural network,.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Theory of the backpropagation neural network,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.036320Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:968648ad2eff2668a483770bf662b3f89c56829d53ebc77ddee6b7199690b78e

Observation 00028661-64c0-4b0f-bbd7-a9c7d89cf1e5 · outbound

This paper cites Morphnet: Fast & simple resource-constrained structure learn- ing of deep networks,.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Morphnet: Fast & simple resource-constrained structure learn- ing of deep networks,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.034659Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:32421eab49f42608b626512c9bbb6982512105089949c1cc7ad93a878737bcf3

Observation a5f29eeb-f704-4a46-a840-4310982ff022 · outbound

This paper cites Why momentum really works,.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Why momentum really works,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.032692Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:871b6aed9cf253c6191329651f21c2dcef283f999198a5e8d50777ca64d60afd

Observation e136c5c2-8c4f-4e48-ada0-eaa80d1fba70 · outbound

This paper cites Attribute proto- type network for zero-shot learning,.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Attribute proto- type network for zero-shot learning,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.028791Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:d736ba974fc71561770a585148f18763bf21d75958f45764c90380b27370ece7

Observation 2c4c6941-c8a1-4d5f-92b0-51a542d02709 · outbound

This paper cites A public domain dataset for human activity recognition using smart- phones,.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems A public domain dataset for human activity recognition using smart- phones,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.006142Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:9237be2a5669a475b06633648c93dd9fcfe3234c70f1054cc6c3d3673ea4faaa

Observation 548f8153-0c6e-4414-8fcc-09e1af4c8355 · outbound

This paper cites Convolutional neural networks for human activity recognition using body-worn sensors,.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Convolutional neural networks for human activity recognition using body-worn sensors,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.032927Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:f8e1c4bc9fb5702e5ddc2c841cc4106401ea8e149a2c0d0a49d375f31a58367f

Observation 269ff49d-9bfb-42c4-831e-c56fbb0daf2d · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library,.

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems Pytorch: An imperative style, high-performance deep learning library,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-07-10T13:47:06.008247Z

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.

source=pdf_text observed=2026-07-10T13:44:13.951954Z digest=sha256:ef5f1c261d04b045c956137c0d1d3a96ad16e0dcfe765549f8cdb90d6461c582

Pith citing papers

No inbound Pith citation observations are available.