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Paper Citation Record · LEDGER

Zeroth-Order Fine-Tuning of LLMs with Extreme Sparsity

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2406.02913.

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

pith.paper-citation-record.v1
2406.02913 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:15:36.828073Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T21:23:44.517430Z

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 f15f567a-b117-4827-9159-2e1a98b191cd · inbound

ElasticZO: A Memory-Efficient On-Device Learning with Combined Zeroth- and First-Order Optimization cites this paper.

ElasticZO: A Memory-Efficient On-Device Learning with Combined Zeroth- and First-Order Optimization Zeroth-Order Fine-Tuning of LLMs with Extreme Sparsity

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-10T21:41:39.617329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:41:39.617329Z digest=sha256:e6007f375ceb6ef8a0d0c23ed528992ed21b88411b07ab9e8aa4ebaad846a2ff

Observation 01b75a96-6839-42fb-853d-8b41f819b58f · inbound

TeZO: Empowering the Low-Rankness on the Temporal Dimension in the Zeroth-Order Optimization for Fine-tuning LLMs cites this paper.

TeZO: Empowering the Low-Rankness on the Temporal Dimension in the Zeroth-Order Optimization for Fine-tuning LLMs Zeroth-Order Fine-Tuning of LLMs with Extreme Sparsity

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-09T21:33:29.677207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T21:33:29.677207Z digest=sha256:a244706668bd3f9b049c6e4966cbb82afd36b6ba382f7043fdf98e83e8d85271

Observation 9b5e9bab-ed59-4b4e-9218-0e92cc4f7b00 · inbound

Elucidating Subspace Perturbation in Zeroth-Order Optimization: Theory and Practice at Scale cites this paper.

Elucidating Subspace Perturbation in Zeroth-Order Optimization: Theory and Practice at Scale Zeroth-Order Fine-Tuning of LLMs with Extreme Sparsity

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-09T21:23:48.541875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T21:23:48.541875Z digest=sha256:2787f868c4801bad9ff34f59b972964c0d7a231e6f515fa99229898d7565a8c3

Observation f169995d-d57c-4451-bb56-f256717cd7a8 · inbound

Mitigating Non-IID Drift in Zeroth-Order Federated LLM Fine-Tuning with Transferable Sparsity cites this paper.

Mitigating Non-IID Drift in Zeroth-Order Federated LLM Fine-Tuning with Transferable Sparsity Zeroth-Order Fine-Tuning of LLMs with Extreme Sparsity

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T11:16:20.416022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:16:20.416022Z digest=sha256:e7d1b41808701be21c3e8a946d624c8810c011216510d8c096ec91ff3c986e88

Observation c4284200-f4fe-4928-8567-39e794d90df7 · inbound

FZOO: Fast Zeroth-Order Optimizer for Fine-Tuning Large Language Models towards Adam-Scale Speed cites this paper.

FZOO: Fast Zeroth-Order Optimizer for Fine-Tuning Large Language Models towards Adam-Scale Speed Zeroth-Order Fine-Tuning of LLMs with Extreme Sparsity

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T05:06:16.307400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:06:16.307400Z digest=sha256:b5c0313fbf1095a6dbe7fd119ca5bea8313f1386060d33e5d4425223b1b56da3

Observation 291479c2-70a0-4ebe-9968-b50b502ea16c · inbound

On the Inherent Privacy of Zeroth Order Projected Gradient Descent cites this paper.

On the Inherent Privacy of Zeroth Order Projected Gradient Descent Zeroth-Order Fine-Tuning of LLMs with Extreme Sparsity

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-06T19:34:03.868625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:34:03.868625Z digest=sha256:fe996da94c606b230010261b8218ecc992a51ffd79739b86dc436dbbc7410359

Observation 4cc1d2d4-768b-478e-8a59-28115aa394b8 · inbound

Learning a Zeroth-Order Optimizer for Fine-Tuning LLMs cites this paper.

Learning a Zeroth-Order Optimizer for Fine-Tuning LLMs Zeroth-Order Fine-Tuning of LLMs with Extreme Sparsity

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-04T13:28:46.722919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T13:28:46.722919Z digest=sha256:105db57e4a08017f66d2f7a76a6fa3793d405ce068dfb77b54cfc23ad1557738

Observation 97dc8962-58b7-4082-8f2e-190e1af79c3b · inbound

Sketching the Readout of Large Language Models for Scalable Data Attribution and Valuation cites this paper.

Sketching the Readout of Large Language Models for Scalable Data Attribution and Valuation Zeroth-Order Fine-Tuning of LLMs with Extreme Sparsity

Reference 17

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T08:48:01.084008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-10T08:47:36.122054Z digest=sha256:ff5c0606af110f0b565a7b2aa2dff8762e64ca111c4c6d4538b83c2b08ba7f77

Observation 4384175e-9d6f-4d92-983c-252d0303a143 · inbound

Sketching the Readout of Large Language Models for Scalable Data Attribution and Valuation cites this paper.

Sketching the Readout of Large Language Models for Scalable Data Attribution and Valuation Zeroth-Order Fine-Tuning of LLMs with Extreme Sparsity

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-02T16:12:08.799813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T16:12:08.799813Z digest=sha256:aeccbb99fa039a8213f61ca0f708b4b568bc0841383c2412da0ace8f490aba30

Observation bcf35b58-9ccf-43b2-baf6-04d2ff77baf7 · 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 Zeroth-Order Fine-Tuning of LLMs with Extreme Sparsity

Reference 54

Resolution
verified exact
arxiv_id, observed 2026-05-11T15:31:07.457710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-05-09T19:50:50.653184Z digest=sha256:7b617f74d950738c8f80f2c7d22742d6c252325a292b526eb68c8e2bc9ab4888

Observation d612a6a8-5bb3-481d-af2a-7b07cd94e12d · inbound

Position: Zeroth-Order Optimization in Deep Learning Is Underexplored, Not Underpowered cites this paper.

Position: Zeroth-Order Optimization in Deep Learning Is Underexplored, Not Underpowered Zeroth-Order Fine-Tuning of LLMs with Extreme Sparsity

Reference 104

Resolution
verified exact
arxiv_id, observed 2026-05-20T21:23:44.518852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-05-20T21:19:55.074853Z digest=sha256:0b6873791bd2ea77f95e07f453a385854ee06c82e6e53fd6b12765812689c7d0

Observation 1077fe27-cc17-437e-b09c-49a4cd414e2c · inbound

Curvature-Aware Zeroth-Order Optimization for Memory-Efficient Test-Time Adaptation cites this paper.

Curvature-Aware Zeroth-Order Optimization for Memory-Efficient Test-Time Adaptation Zeroth-Order Fine-Tuning of LLMs with Extreme Sparsity

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-16T00:15:36.828073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:15:36.828073Z digest=sha256:69cd3439ae7f7fd87307a5a8159e7b1c2d931a6d547c4a193dd17733d0bc301d