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Paper Citation Record · LEDGER

DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2310.02025.

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

pith.paper-citation-record.v1
2310.02025 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:33:07.641230Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-25T07:35:28.902200Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 977b89b3-1b0d-42b5-a137-606f9053807d · inbound

PacTrain: Pruning and Adaptive Sparse Gradient Compression for Efficient Collective Communication in Distributed Deep Learning cites this paper.

PacTrain: Pruning and Adaptive Sparse Gradient Compression for Efficient Collective Communication in Distributed Deep Learning DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T14:33:07.641230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:33:07.641230Z digest=sha256:30d8cb6e5097677a62e74ea996ebdee2e23ebbf58a96964276f9f0d6aca11485

Observation 8c0fe944-2af5-434c-858a-b24577297bc0 · inbound

KerZOO: Kernel Function Informed Zeroth-Order Optimization for Accurate and Accelerated LLM Fine-Tuning cites this paper.

KerZOO: Kernel Function Informed Zeroth-Order Optimization for Accurate and Accelerated LLM Fine-Tuning DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T14:29:34.779580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:29:34.779580Z digest=sha256:95030658b18d1bfcce8387e6638c90816271156f33c57cc965334b0b1b51a78f

Observation 8c03a571-4072-4ece-9fa7-e8be4a1c272f · inbound

PLA: Prompt Learning Attack against Text-to-Image Generative Models cites this paper.

PLA: Prompt Learning Attack against Text-to-Image Generative Models DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T17:42:49.015546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:42:49.015546Z digest=sha256:bdc08868764d15302926ceb232be91df67ecbe7678c09ca8df9156fc6a857573

Observation db565dd3-89ec-445b-af5e-82335d74e6ae · inbound

Low-rank surrogate modeling and stochastic zero-order optimization for training of neural networks with black-box layers cites this paper.

Low-rank surrogate modeling and stochastic zero-order optimization for training of neural networks with black-box layers DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-18T15:26:33.674901Z

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=2026-05-18T15:25:21.814232Z digest=sha256:1ed0d9d3cb009d4f17368d05f58176e17237a7a84cff965df7bd8c6b94de8c1d

Observation c2f8a483-db03-4867-86ee-6c01787f4a97 · inbound

AGZO: Activation-Guided Zeroth-Order Optimization for LLM Fine-Tuning cites this paper.

AGZO: Activation-Guided Zeroth-Order Optimization for LLM Fine-Tuning DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-25T07:35:28.905831Z

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=2026-05-25T07:32:11.750655Z digest=sha256:b1f2f5c85a95b3f55e0a3bea6a6521f064cbb804f143e105b8767614cf5d1269

Observation 5cc832f0-051a-4c04-9e6e-bdf50d7544fd · inbound

AdaMeZO: Adam-style Zeroth-Order Optimizer for LLM Fine-tuning Without Maintaining the Moments cites this paper.

AdaMeZO: Adam-style Zeroth-Order Optimizer for LLM Fine-tuning Without Maintaining the Moments DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training

Reference 68

Resolution
verified exact
arxiv_id, observed 2026-05-11T15:31:07.633995Z

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=arxiv_source observed=2026-05-09T19:50:50.653184Z digest=sha256:3039fb94275217dbae55fc6c6ba96de39d5d7679c34aa50bec8a5103d1c35fb1