Paper Citation Record · LEDGER

QScheduler: Adaptive Gradient Sampling for Zeroth-Order On-Device Training on INT8 NPUs

As of 8 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2607.18802.

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

pith.paper-citation-record.v1
2607.18802 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T14:20:29.363059Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

18 of 18 outbound references displayed

verified exact0
verified fuzzy0
unresolved18
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 24e497ea-13a6-45a3-9d73-55f42bae90e1 · outbound

This paper cites MCUNet: Tiny deep learning on IoT devices,.

QScheduler: Adaptive Gradient Sampling for Zeroth-Order On-Device Training on INT8 NPUs MCUNet: Tiny deep learning on IoT devices,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T14:20:27.234268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6a1969b-5349-42d7-9add-41d6457898bf · outbound

This paper cites A Survey of Quantization Methods for Efficient Neural Network Inference.

QScheduler: Adaptive Gradient Sampling for Zeroth-Order On-Device Training on INT8 NPUs A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T14:20:27.328655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7bc437da-0677-40d9-b4a4-9f99f1b9d589 · outbound

This paper cites TinyTL: Reduce memory, not parameters for efficient on-device learn- ing,.

QScheduler: Adaptive Gradient Sampling for Zeroth-Order On-Device Training on INT8 NPUs TinyTL: Reduce memory, not parameters for efficient on-device learn- ing,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T14:20:27.445559Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4a4c895-f551-4630-9668-a12f3b0771ec · outbound

This paper cites Memory-efficient patch-based inference for tiny deep learning,.

QScheduler: Adaptive Gradient Sampling for Zeroth-Order On-Device Training on INT8 NPUs Memory-efficient patch-based inference for tiny deep learning,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T14:20:27.543308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc04c3d2-7f62-4896-b83f-6dd0cf4f3e8d · outbound

This paper cites TinyOL: TinyML with online-learning on microcontrollers,.

QScheduler: Adaptive Gradient Sampling for Zeroth-Order On-Device Training on INT8 NPUs TinyOL: TinyML with online-learning on microcontrollers,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T14:20:27.615923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53da0bca-ea95-4d39-8920-1fa0255eccba · outbound

This paper cites Learning representations by back-propagating errors,.

QScheduler: Adaptive Gradient Sampling for Zeroth-Order On-Device Training on INT8 NPUs Learning representations by back-propagating errors,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T14:20:27.680585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 72d680ff-cbf5-4acb-bbf6-d12a20827dfc · outbound

This paper cites Stepping forward on the last mile,.

QScheduler: Adaptive Gradient Sampling for Zeroth-Order On-Device Training on INT8 NPUs Stepping forward on the last mile,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T14:20:27.753089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b39301b7-ac54-4514-be1c-b2e0f0eff17a · outbound

This paper cites Training Deep Nets with Sublinear Memory Cost.

QScheduler: Adaptive Gradient Sampling for Zeroth-Order On-Device Training on INT8 NPUs Training Deep Nets with Sublinear Memory Cost

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T14:20:27.960956Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f9a1e06-8d7d-4d6a-a975-f3ad74aca479 · outbound

This paper cites POET: Training neural networks on tiny devices with integrated rematerialization and paging,.

QScheduler: Adaptive Gradient Sampling for Zeroth-Order On-Device Training on INT8 NPUs POET: Training neural networks on tiny devices with integrated rematerialization and paging,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T14:20:28.155480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c1dfeea-d008-4c52-baaa-7b666df60bd5 · outbound

This paper cites Random gradient-free minimization of convex functions,.

QScheduler: Adaptive Gradient Sampling for Zeroth-Order On-Device Training on INT8 NPUs Random gradient-free minimization of convex functions,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T14:20:28.310267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9223ed58-602c-48df-b619-836b6c8005a1 · outbound

This paper cites Multivariate stochastic approximation using a simultaneous perturbation gradient approximation,.

QScheduler: Adaptive Gradient Sampling for Zeroth-Order On-Device Training on INT8 NPUs Multivariate stochastic approximation using a simultaneous perturbation gradient approximation,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T14:20:28.445159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c2c27e5-3b55-4a5c-b54b-30868d89a6b4 · outbound

This paper cites On-device training under 256KB memory,.

QScheduler: Adaptive Gradient Sampling for Zeroth-Order On-Device Training on INT8 NPUs On-device training under 256KB memory,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T14:20:28.563098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28ceef89-b1a8-4998-8385-1c7be35b316f · outbound

This paper cites Fine-tuning language models with just forward passes,.

QScheduler: Adaptive Gradient Sampling for Zeroth-Order On-Device Training on INT8 NPUs Fine-tuning language models with just forward passes,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T14:20:28.639797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b0cff78-55f8-483a-a86d-4943ca8e0dd2 · outbound

This paper cites Adam: A method for stochas- tic optimization,.

QScheduler: Adaptive Gradient Sampling for Zeroth-Order On-Device Training on INT8 NPUs Adam: A method for stochas- tic optimization,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T14:20:28.718262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 820ae85e-d78c-44d9-9253-4ea1a3101221 · outbound

This paper cites Eu- rosat: A novel dataset and deep learning benchmark for land use and land cover classification,.

QScheduler: Adaptive Gradient Sampling for Zeroth-Order On-Device Training on INT8 NPUs Eu- rosat: A novel dataset and deep learning benchmark for land use and land cover classification,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T14:20:28.897072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce28588b-20da-47b1-ab32-7cc8dcbca1fc · outbound

This paper cites An analysis of single- layer networks in unsupervised feature learning,.

QScheduler: Adaptive Gradient Sampling for Zeroth-Order On-Device Training on INT8 NPUs An analysis of single- layer networks in unsupervised feature learning,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T14:20:29.117411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42506206-7bcb-48fd-8165-e9ed0c560197 · outbound

This paper cites Practical bayesian optimization of machine learning hyperparam- eters,.

QScheduler: Adaptive Gradient Sampling for Zeroth-Order On-Device Training on INT8 NPUs Practical bayesian optimization of machine learning hyperparam- eters,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T14:20:29.262564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe9fe6d8-1d56-4c6f-a444-c36ef0a78bef · outbound

This paper cites an unresolved cited work.

QScheduler: Adaptive Gradient Sampling for Zeroth-Order On-Device Training on INT8 NPUs Unresolved cited work

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T14:20:29.363059Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.