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Zhiyuan Zeng

Paul G. Allen School of Computer Science & Engineering, University of Washington

10 papers hereh-index 81.2k citations12 works total

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

author position
  • first author3
  • middle author7

Across the 10 of 10 papers where every author was matched, so the position is known.

fields
  • cs.CL8
  • cs.LG2
affiliations
  • Paul G. Allen School of Computer Science & Engineering, University of Washington
Homepage
same name
  • Zhiyuan Zeng — 13 papers, h 9
  • Zhiyuan Zeng — 10 papers, h 7
  • Zhiyuan Zeng — 6 papers, h 8
  • Zhiyuan Zeng — 1 paper, h 56

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 citedSheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning

20 citations · 33 across the 8 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

cs.CL2023★ 11 cited

Evaluating Large Language Models at Evaluating Instruction Following

Zhiyuan Zeng, Jiatong Yu, Tianyu Gao +3

As research in large language models (LLMs) continues to accelerate, LLM-based evaluation has emerged as a scalable and cost-effective alternative to human evaluations for comparin…

cs.CL2023★ 20 cited

Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning

Mengzhou Xia, Tianyu Gao, Zhiyuan Zeng +1

The popularity of LLaMA (Touvron et al., 2023a;b) and other recently emerged moderate-sized large language models (LLMs) highlights the potential of building smaller yet powerful L…

cs.CL2023★ 2 cited

Emergent Modularity in Pre-trained Transformers

Zhengyan Zhang, Zhiyuan Zeng, Yankai Lin +7

This work examines the presence of modularity in pre-trained Transformers, a feature commonly found in human brains and thought to be vital for general intelligence. In analogy to…

cs.CL2023

Plug-and-Play Knowledge Injection for Pre-trained Language Models

Zhengyan Zhang, Zhiyuan Zeng, Yankai Lin +8

Injecting external knowledge can improve the performance of pre-trained language models (PLMs) on various downstream NLP tasks. However, massive retraining is required to deploy ne…

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