TeZO: Empowering the Low-Rankness on the Temporal Dimension in the Zeroth-Order Optimization for Fine-Tuning LLMs.
- DOI
- 10.1109/tpami.2026.3734392
- Published
- 2026 Sep 15
- Container
- IEEE transactions on pattern analysis and machine intelligence
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/tpami.2026.3734392,
title = {TeZO: Empowering the Low-Rankness on the Temporal Dimension in the Zeroth-Order Optimization for Fine-Tuning LLMs.},
author = {Sun Y and Zhang Q and Ding L and Shen L and Tao D},
year = {2026},
journal = {IEEE transactions on pattern analysis and machine intelligence},
doi = {10.1109/tpami.2026.3734392},
url = {https://doi.org/10.1109/tpami.2026.3734392}
}RIS
TY - JOUR TI - TeZO: Empowering the Low-Rankness on the Temporal Dimension in the Zeroth-Order Optimization for Fine-Tuning LLMs. AU - Sun Y AU - Zhang Q AU - Ding L AU - Shen L AU - Tao D PY - 2026 JO - IEEE transactions on pattern analysis and machine intelligence DO - 10.1109/tpami.2026.3734392 UR - https://doi.org/10.1109/tpami.2026.3734392 ER -
APA
Y, S., Q, Z., L, D., L, S., & D, T. (2026). TeZO: Empowering the Low-Rankness on the Temporal Dimension in the Zeroth-Order Optimization for Fine-Tuning LLMs.. IEEE transactions on pattern analysis and machine intelligence. https://doi.org/10.1109/tpami.2026.3734392
Source records
- pubmed · retrieved 2026-09-25T12:19:04.893Z