Paper Citation Record · LEDGER

Enhancing Zeroth-order Fine-tuning for Language Models with Low-rank Structures

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2410.07698.

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

pith.paper-citation-record.v1
2410.07698 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 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 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T21:33:29.660302Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T17:08:43.670348Z

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 5dba745c-cd70-4cb3-9093-0be6233c4e50 · 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 Enhancing Zeroth-order Fine-tuning for Language Models with Low-rank Structures

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-09T21:33:29.660302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df6583af-2229-478b-af51-b34e54458b07 · 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 Enhancing Zeroth-order Fine-tuning for Language Models with Low-rank Structures

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-09T21:23:48.487339Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3416b57f-a747-44e1-aa4f-53cd5a854338 · inbound

A Memory Efficient Randomized Subspace Optimization Method for Training Large Language Models cites this paper.

A Memory Efficient Randomized Subspace Optimization Method for Training Large Language Models Enhancing Zeroth-order Fine-tuning for Language Models with Low-rank Structures

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-08T13:31:42.057316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35bdf3e2-071b-4dd9-a96c-d43b08afd38a · 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 Enhancing Zeroth-order Fine-tuning for Language Models with Low-rank Structures

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T05:06:15.802479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95b7e784-4094-479f-b626-8868187e7af5 · inbound

From PowerSGD to PowerSGD+: Low-Rank Gradient Compression for Distributed Optimization with Convergence Guarantees cites this paper.

From PowerSGD to PowerSGD+: Low-Rank Gradient Compression for Distributed Optimization with Convergence Guarantees Enhancing Zeroth-order Fine-tuning for Language Models with Low-rank Structures

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T17:01:42.042592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd77e3b3-7c1f-4d02-a5d1-2d5d641a31f8 · 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 Enhancing Zeroth-order Fine-tuning for Language Models with Low-rank Structures

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-18T15:26:33.700127Z

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.

Observation 091a9375-e394-4e1a-8b28-fb92414d4c84 · inbound

CR-Net: Scaling Parameter-Efficient Training with Cross-Layer Low-Rank Structure cites this paper.

CR-Net: Scaling Parameter-Efficient Training with Cross-Layer Low-Rank Structure Enhancing Zeroth-order Fine-tuning for Language Models with Low-rank Structures

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-18T14:52:41.113524Z

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.

Observation cde177c8-cc59-4591-b6f0-d41ce197c7cd · inbound

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

Learning a Zeroth-Order Optimizer for Fine-Tuning LLMs Enhancing Zeroth-order Fine-tuning for Language Models with Low-rank Structures

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T13:28:45.687627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbe0a637-8f02-4d93-bdf1-99e2c82a508e · 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 Enhancing Zeroth-order Fine-tuning for Language Models with Low-rank Structures

Reference 55

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:31:07.429916Z

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.

Observation 9060aa58-b199-401e-9c37-a7d50ffcbff6 · inbound

Accelerating Zeroth-Order Spectral Optimization with Partial Orthogonalization from Power Iteration cites this paper.

Accelerating Zeroth-Order Spectral Optimization with Partial Orthogonalization from Power Iteration Enhancing Zeroth-order Fine-tuning for Language Models with Low-rank Structures

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-12T02:21:16.991591Z

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.

Observation b29acf24-b66c-4753-b40e-a692ded2ce3e · inbound

Accelerating Zeroth-Order Spectral Optimization with Partial Orthogonalization from Power Iteration cites this paper.

Accelerating Zeroth-Order Spectral Optimization with Partial Orthogonalization from Power Iteration Enhancing Zeroth-order Fine-tuning for Language Models with Low-rank Structures

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-19T17:33:09.404759Z

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.

Observation 398d9924-14e5-4c58-8b17-4af6b8479684 · inbound

Dominant-Layer ZO: A Single Layer Dominates Zeroth-Order Fine-Tuning of LLMs cites this paper.

Dominant-Layer ZO: A Single Layer Dominates Zeroth-Order Fine-Tuning of LLMs Enhancing Zeroth-order Fine-tuning for Language Models with Low-rank Structures

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-07-02T07:56:46.996581Z

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.

Observation 3ee2334a-af43-4896-b5eb-dedfc0ab874d · inbound

Zero-order Parameter-free Optimization for LMO-based Methods: Novel Approach for Efficient Fine-tuning cites this paper.

Zero-order Parameter-free Optimization for LMO-based Methods: Novel Approach for Efficient Fine-tuning Enhancing Zeroth-order Fine-tuning for Language Models with Low-rank Structures

Reference 81

Resolution: verified exact; arxiv_id, observed 2026-07-03T17:08:43.671804Z

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.

Observation c699db8b-2eaa-461d-bc9f-e56a38af15e1 · inbound

RED-SEGA:Resilient Decentralized Stochastic Proximal Optimization with Gradient Sketching over Time-Varying Networks cites this paper.

RED-SEGA:Resilient Decentralized Stochastic Proximal Optimization with Gradient Sketching over Time-Varying Networks Enhancing Zeroth-order Fine-tuning for Language Models with Low-rank Structures

Reference 36

Resolution: unresolved; no resolver link, observed 2026-07-14T09:14:06.532791Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.