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Rongyu Zhang

19 papers hereh-index 8214 citations28 works total

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

author position
  • first author6
  • middle author10

Across the 16 of 19 papers where every author was matched, so the position is known.

fields
  • cs.CV8
  • cs.LG4
  • cs.RO4
  • cs.AI1
  • cs.CE1
  • cs.CL1
same name
  • Rongyu Zhang — 8 papers, h 5
  • Rongyu Zhang — 5 papers, h 5
  • Rongyu Zhang — 3 papers, h 6
  • Rongyu Zhang — 1 paper, h 1

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
20232026
most citedEfficient Deweather Mixture-of-Experts with Uncertainty-aware Feature-wise Linear Modulation

3 citations · 7 across the 19 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2026

Key-Embedded Privacy for Decentralized AI in Biomedical Omics

Rongyu Zhang, Hongyu Dong, Gaole Dai +13

The rapid adoption of data-driven methods in biomedicine has intensified concerns over privacy, governance, and regulation, limiting raw data sharing and hindering the assembly of…

cs.LG2025

FBQuant: FeedBack Quantization for Large Language Models

Yijiang Liu, Hengyu Fang, Liulu He +4

Deploying Large Language Models (LLMs) on edge devices is increasingly important, as it eliminates reliance on network connections, reduces expensive API calls, and enhances user p…

cs.LG2024

PAT: Pruning-Aware Tuning for Large Language Models

Yijiang Liu, Huanrui Yang, Youxin Chen +4

Large language models (LLMs) excel in language tasks, especially with supervised fine-tuning after pre-training. However, their substantial memory and computational requirements hi…

cs.LG2024

T-REX: Mixture-of-Rank-One-Experts with Semantic-aware Intuition for Multi-task Large Language Model Finetuning

Rongyu Zhang, Yijiang Liu, Huanrui Yang +5

Large language models (LLMs) encounter significant adaptation challenges in diverse multitask finetuning. Mixture-of-experts (MoE) provides a promising solution with a dynamic arch…

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