Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
TeZO: Empowering the Low-Rankness on the Temporal Dimension in the Zeroth-Order Optimization for Fine-tuning LLMs
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2501.19057.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T05:06:18.054020Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T15:31:07.435202Z
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 6e76a80a-b0e6-44fe-ac7a-e0d00ebef3bd · 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 TeZO: Empowering the Low-Rankness on the Temporal Dimension in the Zeroth-Order Optimization for Fine-tuning LLMs
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T05:06:18.054020Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 15714c68-19ad-4a56-b90b-b95a89e545e4 · inbound
Learning a Zeroth-Order Optimizer for Fine-Tuning LLMs cites this paper.
Learning a Zeroth-Order Optimizer for Fine-Tuning LLMs TeZO: Empowering the Low-Rankness on the Temporal Dimension in the Zeroth-Order Optimization for Fine-tuning LLMs
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T13:28:49.295868Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0f15c1d8-e7f1-420c-90fc-5eacd80242f0 · inbound
Evolution of Optimization Methods: Algorithms, Scenarios, and Evaluations cites this paper.
Evolution of Optimization Methods: Algorithms, Scenarios, and Evaluations TeZO: Empowering the Low-Rankness on the Temporal Dimension in the Zeroth-Order Optimization for Fine-tuning LLMs
Reference 30
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T10:51:22.306073Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation e498798a-305d-4609-b58c-923de490b436 · inbound
Universally Empowering Zeroth-Order Optimization via Adaptive Layer-wise Sampling cites this paper.
Universally Empowering Zeroth-Order Optimization via Adaptive Layer-wise Sampling TeZO: Empowering the Low-Rankness on the Temporal Dimension in the Zeroth-Order Optimization for Fine-tuning LLMs
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T11:30:19.657864Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 62f7d2df-c49f-449e-a436-b18cb61dd784 · 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 TeZO: Empowering the Low-Rankness on the Temporal Dimension in the Zeroth-Order Optimization for Fine-tuning LLMs
Reference 59
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T15:31:07.441349Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.