Paper Citation Record · LEDGER

Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2402.11592.

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

pith.paper-citation-record.v1
2402.11592 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:21:16.047255Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

7
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e88e99eb-a13e-438e-bd1a-df8983cf1165 · inbound

DistZO2: High-Throughput and Memory-Efficient Zeroth-Order Fine-tuning LLMs with Distributed Parallel Computing cites this paper.

DistZO2: High-Throughput and Memory-Efficient Zeroth-Order Fine-tuning LLMs with Distributed Parallel Computing Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-06T20:21:16.047255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27ef8ba7-c15d-4a43-a49a-34d8a6c0fe17 · inbound

Downgrade to Upgrade: Optimizer Simplification Enhances Robustness in LLM Unlearning cites this paper.

Downgrade to Upgrade: Optimizer Simplification Enhances Robustness in LLM Unlearning Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-18T10:46:17.015883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 421c3e76-3a6e-4b97-b153-3dfd3a5e5d10 · 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 Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark

Reference 67

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:31:07.694278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b8613502-c2b1-4242-9577-41e10cd34377 · 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 Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-12T02:21:16.987973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 03159599-d291-41e2-959c-2dabce081acb · 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 Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-19T17:33:09.415526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 59bc413f-0df6-4605-9fb1-2933ba2849f7 · inbound

REALISTA: Realistic Latent Adversarial Attacks that Elicit LLM Hallucinations cites this paper.

REALISTA: Realistic Latent Adversarial Attacks that Elicit LLM Hallucinations Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark

Reference 165

Resolution: metadata mismatch; arxiv_id, observed 2026-05-14T20:17:56.406876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0747e701-97a6-4a06-93d8-8e2518ad3d43 · inbound

Aligned but Fragile: Enhancing LLM Safety Robustness via Zeroth-Order Optimization cites this paper.

Aligned but Fragile: Enhancing LLM Safety Robustness via Zeroth-Order Optimization Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-06-29T07:43:13.504065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e2714054-638f-4f98-aac9-132686073e6d · inbound

ZOAF: Towards Efficient Zeroth-Order Optimization for Analog/RF Circuit Design cites this paper.

ZOAF: Towards Efficient Zeroth-Order Optimization for Analog/RF Circuit Design Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-07-02T01:36:25.829808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f3349ea5-1e68-4fad-b132-c063a6b24297 · inbound

A Unified Zeroth-Order Approach for Decentralized Minimax Optimization cites this paper.

A Unified Zeroth-Order Approach for Decentralized Minimax Optimization Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-07-03T12:48:11.286780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f18c73d5-fe78-446d-b670-18b3500ef573 · inbound

SENTINEL: Failure-Driven Reinforcement Learning for Training Tool-Using Language Model Agents cites this paper.

SENTINEL: Failure-Driven Reinforcement Learning for Training Tool-Using Language Model Agents Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-07-03T14:58:33.254580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2fae1f09-758b-4ac9-a725-8cf2da046258 · 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 Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-07-03T17:08:43.635387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1cc15aa5-8a0b-49f9-9c0c-119580b32093 · inbound

Probing Memorization of Tabular In-Context Learning cites this paper.

Probing Memorization of Tabular In-Context Learning Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-07-01T09:05:37.602036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation eb90faae-c79c-438d-8300-798117c23af2 · inbound

OmniOpt: Taxonomy, Geometry, and Benchmarking of Modern Optimizers cites this paper.

OmniOpt: Taxonomy, Geometry, and Benchmarking of Modern Optimizers Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark

Reference 135

Resolution: unresolved; no resolver link, observed 2026-07-11T22:10:49.683444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.