Pith. sign in

Paper Citation Record · LEDGER

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees

As of 9 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2506.11391.

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

pith.paper-citation-record.v1
2506.11391 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:21:46.390087Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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 exact1
  • verified fuzzy29
  • unresolved5
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f82a3658-9eeb-4de0-92fd-03390e71d150 · outbound

This paper cites Edge artificial intelligence for 6G: Vision, enabling technologies, and applications,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Edge artificial intelligence for 6G: Vision, enabling technologies, and applications,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.661892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.316740Z digest=sha256:7bdf49cb4bbebadb81f0ee885816b068600ac62a3ee01052f5d40aa717422dc9

Observation 8563a5e9-a5e2-4aed-ae35-d0195fc3ed2c · outbound

This paper cites Wireless 6G connectivity for massive number of devices and critical services,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Wireless 6G connectivity for massive number of devices and critical services,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.654522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.319469Z digest=sha256:3b78a311f2ff3a268357ca2a20fa95868a8d82b332fd8c06ccd22c49addc1348

Observation 41a7d371-6480-4da3-acdf-a6eb95eb608e · outbound

This paper cites Mobile edge intelligence and computing for the Internet of vehicles,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Mobile edge intelligence and computing for the Internet of vehicles,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.646548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.321780Z digest=sha256:e105220ac8a8fdcf7dbf8723b0627ce4d421c9e6a2b1ec17e907e6746ec87f35

Observation 32599f0d-7ba1-4cf4-a2aa-8f7c5f4499e4 · outbound

This paper cites Knowledge-based ultra-low-latency semantic communications for robotic edge intelligence,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Knowledge-based ultra-low-latency semantic communications for robotic edge intelligence,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.638415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.324129Z digest=sha256:4975fde4a12d0e30a7705eaa25bf2318f2cac460001a5b5c82175011f372c4f3

Observation 421509c5-7bf9-41f5-8347-3c60a45d8805 · outbound

This paper cites Service requirements for cyber-physical control applications in vertical domains,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Service requirements for cyber-physical control applications in vertical domains,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.631271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.326425Z digest=sha256:910fdebe6e1227561b59bc427513f59fbf016acfc94a30511cf3535d4cb4e3ca

Observation 7b047224-baa4-4940-ab53-8a4dc0817213 · outbound

This paper cites EfficientNet: Rethinking model scaling for convolu- tional neural networks,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees EfficientNet: Rethinking model scaling for convolu- tional neural networks,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.624047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.328536Z digest=sha256:d87ea60bebbddddb1db6d836939cc9906b92336726dbcfb9db2bb47be8824fa7

Observation 1d610f1a-9f66-4f1d-9290-417bce5292b3 · outbound

This paper cites Conformal prediction: A gentle introduction,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Conformal prediction: A gentle introduction,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.616710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.330926Z digest=sha256:7b481f86b85528cef4bbe34a8188fab341a4d01add1008b3b3a5a4362db42696

Observation 87354fd9-99fc-4a4c-8859-19dc28f81d16 · outbound

This paper cites Conformal risk control,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Conformal risk control,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.609444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.332975Z digest=sha256:2910bc46654535ddf36c29c15901affe0bad6f1d64123b12f84921551a7bff11

Observation 00eac099-32a4-4b72-a981-281078cf966d · outbound

This paper cites Prediction-powered inference,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Prediction-powered inference,

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T04:21:46.335191Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:21:46.335191Z digest=sha256:3112996553707bff886a10c9edaa81079b68d625d5478b49a6d0ed21b6aaf795

Observation 1f37062c-9cd7-4762-87e4-011e24a68087 · outbound

This paper cites Communication-computation trade-off in resource-constrained edge inference,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Communication-computation trade-off in resource-constrained edge inference,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.599022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.337149Z digest=sha256:80a1e97076fd662e9cba0b41c7ea00467f40711336db6b45271f83a30a50ee62

Observation 02469823-5adc-4206-b169-7c77871f3a64 · outbound

This paper cites Dynamic compression ratio selection for edge inference systems with hard deadlines,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Dynamic compression ratio selection for edge inference systems with hard deadlines,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.592302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.339093Z digest=sha256:58b43ec37a9a96dfdf7f09e6fb0e39149c55520a8dddd88cacabae9c6f929e68

Observation f8eaf478-775f-4cc0-b55e-6ac73a4311ec · outbound

This paper cites Edge AI: On-demand acceler- ating deep neural network inference via edge computing,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Edge AI: On-demand acceler- ating deep neural network inference via edge computing,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.585092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.341377Z digest=sha256:b28175c7b2bc7edc82420da96ad81b5fc0283c750eedf0741e901227912a83b6

Observation 7e8ce209-fc76-454e-a591-835aef015759 · outbound

This paper cites JALAD: Joint accuracy-and latency-aware deep structure decoupling for edge-cloud execution,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees JALAD: Joint accuracy-and latency-aware deep structure decoupling for edge-cloud execution,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.576234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.343606Z digest=sha256:f5ecc57b811f052ac45fe7ffefb056f62c2e04573c430d673b0b2a01096d44fb

Observation 80cf7ccb-2d39-43dc-b7fd-bfbddf25f616 · outbound

This paper cites Joint device-edge inference over wireless links with pruning,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Joint device-edge inference over wireless links with pruning,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.568736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.345510Z digest=sha256:8c6da56fa3a73d1ae342be58aeb491961f77595f50f451d6bd2237f882fe8e6a

Observation be4f2c16-d515-4e2a-8b06-01a767fedc6c · outbound

This paper cites Wireless image retrieval at the edge,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Wireless image retrieval at the edge,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.561587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.347487Z digest=sha256:308f7e16573eac6ef96b2f03eefffe3c237e4961a4c2d1f03ab372b05001dc96

Observation c99a325e-94fa-467a-a4cd-57f1566cb2b1 · outbound

This paper cites Ultra-Low-Latency Edge Inference for Distributed Sensing.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Ultra-Low-Latency Edge Inference for Distributed Sensing

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T04:21:46.349651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:21:46.349651Z digest=sha256:ff96922eb4f7bf3af5d390600e90184b3ebac4b1481bd7175a468a3564eb3fd9

Observation 31ec5c32-160a-4d53-b115-7f0485abf2da · outbound

This paper cites Ultra-Low-Latency Edge Intelligent Sensing: A Source-Channel Tradeoff and Its Application to Coding Rate Adaptation.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Ultra-Low-Latency Edge Intelligent Sensing: A Source-Channel Tradeoff and Its Application to Coding Rate Adaptation

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-08-07T04:21:46.433288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.351838Z digest=sha256:a8d641a5f5b78aa18ecf5f3c5ba5d10bd0db7bff715bf04dd53ef8372fc18711

Observation 2d442c66-65e3-43ef-9ac7-0751d707c2c9 · outbound

This paper cites Resource allocation for multiuser edge inference with batching and early exiting,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Resource allocation for multiuser edge inference with batching and early exiting,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.553256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.354527Z digest=sha256:6eef30fc5fb11bef06a3784f7209cce59af9c23ad4141299cb2d75132b663d4d

Observation 0c237a71-1a37-4786-9c92-e0e64e9fa02a · outbound

This paper cites On-demand edge inference scheduling with accuracy and deadline guarantee,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees On-demand edge inference scheduling with accuracy and deadline guarantee,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.546197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.356712Z digest=sha256:261da5e92a9fdfe34c4cce9d7abc055fc8da38fdae6a47a961c48541b20e484f

Observation e8cb45e7-1525-4e79-b462-ef50b8b4cd00 · outbound

This paper cites Adaptive early exiting for collaborative inference over noisy wireless channels,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Adaptive early exiting for collaborative inference over noisy wireless channels,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.538141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.358653Z digest=sha256:27fe14fa901cda8ad186921d522c282c16d7acca909a91de3132fe4e4fa76c3e

Observation d55f2b9e-fefa-43d1-b061-58030c475292 · outbound

This paper cites Over-the- air multi-view pooling for distributed sensing,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Over-the- air multi-view pooling for distributed sensing,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.530974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.360586Z digest=sha256:eeaa06736ed052bbea9a2d48f0f03c2e06b53a02a557b55f32f3850a9341f74d

Observation ad4e210c-fcb6-49a8-ad3e-73b9cc6e1e9f · outbound

This paper cites Progressive feature transmission for split classification at the wireless edge,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Progressive feature transmission for split classification at the wireless edge,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.523831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.362543Z digest=sha256:463e5c35909471521e30cc60e9802fdab044e81d49f5a70dc4e6403887b37134

Observation ec7b029b-3f9b-4045-bdc3-645fa892b00c · outbound

This paper cites Beyond the cloud: Edge inference for generative large language models in wireless networks,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Beyond the cloud: Edge inference for generative large language models in wireless networks,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.516011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.364346Z digest=sha256:922407fccd36b62b961afcfaf26b464432359035377017a5d075a3ea43899340

Observation bc7c9da4-c996-45d7-8ba2-58bf6304968b · outbound

This paper cites Guaranteed dynamic scheduling of ultra-reliable low-latency traffic via conformal prediction,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Guaranteed dynamic scheduling of ultra-reliable low-latency traffic via conformal prediction,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.508011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.366254Z digest=sha256:4a41fe9b4f1ac713e0cecd75593e20508ee9d13c28d7a38bfff3cd4116f8382a

Observation 3e4f6d2c-8d3e-4f4b-81a0-8c4cc5071b39 · outbound

This paper cites Calibrating AI models for wireless communications via conformal prediction,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Calibrating AI models for wireless communications via conformal prediction,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.501046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.368491Z digest=sha256:543154dc452966623b6536e6876e55e0bf6707aabcd34d7954e75c740f92daa3

Observation e402d2e0-4106-413f-9509-6c073cbdd018 · outbound

This paper cites Fed- erated inference with reliable uncertainty quantification over wireless channels via conformal prediction,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Fed- erated inference with reliable uncertainty quantification over wireless channels via conformal prediction,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.493670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.370266Z digest=sha256:ad1324c4dd1a1a75aa7aac16607c4ba2ff6f64fe5644989ebf9065d7f5d42fa2

Observation 8b1f0240-75cd-4b81-8cc7-35371f079307 · outbound

This paper cites Branchynet: Fast inference via early exiting from deep neural networks,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Branchynet: Fast inference via early exiting from deep neural networks,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.485913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.372612Z digest=sha256:01fbaccdd236dabfe556fd58ddec032c77b103075da1366f8a934d8d0ca0ff58

Observation 55d85924-6c52-4187-ba8c-6a2fb82cc791 · outbound

This paper cites YOLOv10: Real-Time End-to-End Object Detection.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees YOLOv10: Real-Time End-to-End Object Detection

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T04:21:46.374594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:21:46.374594Z digest=sha256:451951a955a9859f5186ac743a6ef5f8746cf24d3b2b9720e5ac2838bb627372

Observation 834c69cc-be44-48c5-8df5-afc993e66cc2 · outbound

This paper cites Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T04:21:46.377283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:21:46.377283Z digest=sha256:49f46ac194665ce4aa90b33c12699b5b22e5c77336534985ac6e79471aa1b394

Observation b7ef6959-02e9-4b2d-93f3-e3cced5687e7 · outbound

This paper cites Adaptive Learn-then-Test: Statistically Valid and Efficient Hyperparameter Selection.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Adaptive Learn-then-Test: Statistically Valid and Efficient Hyperparameter Selection

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T04:21:46.379725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:21:46.379725Z digest=sha256:55ac055bc9909fb7040a274239b17a42d57b43b0708ab3cc9655de48c2ac433e

Observation f5001939-44b4-48f2-a9e5-b474111bd57b · outbound

This paper cites ImageNet large scale visual recognition chal- lenge,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees ImageNet large scale visual recognition chal- lenge,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.478561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.381872Z digest=sha256:58eacd175fb4570f9cca4403e0caedb6a504b0eeafe855b79355caa8ed93c9ca

Observation 338c0385-6ef6-4962-beab-097a07645d80 · outbound

This paper cites WebP image format,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees WebP image format,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.470490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.383789Z digest=sha256:35ae67ed530efddc0b6f623c87aaf97c21000950675d96359420ce07770e7e4c

Observation 14321d9a-ad50-41db-87dd-64f33ac8ea59 · outbound

This paper cites EfficientNetV2: Smaller models and faster training,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees EfficientNetV2: Smaller models and faster training,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.455287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.388117Z digest=sha256:dab890b147a35d7d7fde9c78cd6c036c1684c8b363fde58e2cdcad574e323cb2

Observation d7059cf8-fcfc-4a07-a802-6a0eedd59ce7 · outbound

This paper cites PyTorch 2: Faster machine learning through dynamic Python bytecode transformation and graph compilation,.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees PyTorch 2: Faster machine learning through dynamic Python bytecode transformation and graph compilation,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.446873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.390087Z digest=sha256:a78b866e8b5c87bfe48d685487d82352dfa5f7798a775107e9ac411626d9f442

Observation dac919f9-08e0-4bd8-91a5-cecdc26cc44a · outbound

This paper cites Available: https://www.rfc-editor.org/info/rfc9649.

Black-Box Edge AI Model Selection with Conformal Latency and Accuracy Guarantees Available: https://www.rfc-editor.org/info/rfc9649

Reference 2024

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T04:21:46.462575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T04:21:46.385910Z digest=sha256:75ad1776e61fae7dfff4f3d1c75a58e182b9df16e4636cd91208cd1e1227ecd8

Pith citing papers

No inbound Pith citation observations are available.