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Jingzhao Zhang

7 papers hereh-index 453 citations8 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author5

Across the 7 of 7 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • cs.CL1
  • cs.CR1
  • eess.SY1
same name
  • Jingzhao Zhang — 9 papers, h 3
  • Jingzhao Zhang — 5 papers, h 3
  • Jingzhao Zhang — 4 papers, h 3
  • Jingzhao Zhang — 4 papers, h 2
  • Jingzhao Zhang — 3 papers
  • Jingzhao Zhang — 2 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232025
most citedRandom Masking Finds Winning Tickets for Parameter Efficient Fine-tuning

1 citations · 2 across the 6 of their papers we have counts for

collaborators
Showing 2025Show all

4 papers · 1 filter

eess.SY2025

Finite Sample Analyses for Continuous-time Linear Systems: System Identification and Online Control

Hongyi Zhou, Jingwei Li, Jingzhao Zhang

Real world evolves in continuous time but computations are done from finite samples. Therefore, we study algorithms using finite observations in continuous-time linear dynamical sy…

cs.CL2025

NeuralDB: Scaling Knowledge Editing in LLMs to 100,000 Facts with Neural KV Database

Weizhi Fei, Hao Shi, Jing Xu +7

Efficiently editing knowledge stored in large language models (LLMs) enables model updates without large-scale training. One possible solution is Locate-and-Edit (L\&E), allowing s…

cs.LG2025

Understanding Nonlinear Implicit Bias via Region Counts in Input Space

Jingwei Li, Jing Xu, Zifan Wang +2

One explanation for the strong generalization ability of neural networks is implicit bias. Yet, the definition and mechanism of implicit bias in non-linear contexts remains little…

cs.LG2025

Scalable Model Merging with Progressive Layer-wise Distillation

Jing Xu, Jiazheng Li, Jingzhao Zhang

Model merging offers an effective way to integrate the capabilities of multiple fine-tuned models. However, the performance degradation of the merged model remains a challenge, par…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.