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Zhongwei Wan

19 papers hereh-index 161.3k citations25 works total

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

author position
  • first author3
  • middle author15

Across the 18 of 19 papers where every author was matched, so the position is known.

fields
  • cs.CL11
  • cs.CV3
  • eess.SP2
  • cs.AI1
  • cs.DC1
  • cs.LG1
same name
  • Zhongwei Wan — 11 papers, h 6
  • Zhongwei Wan — 10 papers, h 6
  • Zhongwei Wan — 7 papers, h 8
  • Zhongwei Wan — 6 papers, h 6
  • Zhongwei Wan — 4 papers, h 3
  • Zhongwei Wan — 3 papers, 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 Large Language Models: A Survey

25 citations · 41 across the 19 of their papers we have counts for

collaborators
Showing 2026Show all

4 papers · 1 filter

cs.CL2026

AgentSpec: Speculative Decoding for Batch Inference of LLM Agents

Xin Wang, Ziming Miao, Yi Zhu +4

Large language model (LLM)-based agent applications often incur high response time. Speculative decoding is a promising solution to improve the inference efficiency of LLM agents w…

cs.CL2026

Dynamic Linear Attention

Xin Wang, Hui Shen, Boyuan Zheng +7

The scalability of Large Language Models (LLMs) to long contexts is fundamentally constrained by the quadratic complexity of standard attention, motivating the adoption of linear a…

cs.LG2026

QuantVLA: Scale-Calibrated Post-Training Quantization for Vision-Language-Action Models

Jingxuan Zhang, Yunta Hsieh, Zhongwei Wan +5

Vision-language-action (VLA) models unify perception, language, and control for embodied agents but face significant challenges in practical deployment due to rapidly increasing co…

cs.CV2026

MMDeepResearch-Bench: A Benchmark for Multimodal Deep Research Agents

Peizhou Huang, Zixuan Zhong, Zhongwei Wan +12

Deep Research Agents (DRAs) generate citation-rich reports via multi-step search and synthesis, yet existing benchmarks mainly target text-only settings or short-form multimodal QA…

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