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Zihang Xu

9 papers hereh-index 4561 citations17 works total

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

author position
  • first author1
  • middle author6
  • last author1

Across the 8 of 9 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.CL3
  • cs.AI1
  • cs.RO1
same name
  • Zihang Xu — 6 papers, h 2
  • Zihang Xu — 4 papers, h 3
  • Zihang Xu — 1 paper, h 0
  • Zihang Xu — 1 paper, h 0
  • Zihang Xu — 1 paper, h 6

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
20242026
most cited∞Bench: Extending Long Context Evaluation Beyond 100K Tokens

2 citations · 3 across the 9 of their papers we have counts for

collaborators
Showing 2025Show all

4 papers · 1 filter

cs.RO2025

Arcadia: Toward a Full-Lifecycle Framework for Embodied Lifelong Learning

Minghe Gao, Juncheng Li, Yuze Lin +15

We contend that embodied learning is fundamentally a lifecycle problem rather than a single-stage optimization. Systems that optimize only one link (data collection, simulation, le…

cs.AI2025

Training-Free Time Series Classification via In-Context Reasoning with LLM Agents

Songyuan Sui, Zihang Xu, Xia Hu

Time series classification (TSC) spans diverse application scenarios, yet labeled data are often scarce, making task-specific training costly and inflexible. Recent reasoning-orien…

cs.CV2025

FideDiff: Efficient Diffusion Model for High-Fidelity Image Motion Deblurring

Xiaoyang Liu, Zhengyan Zhou, Zihang Xu +3

Recent advancements in image motion deblurring, driven by CNNs and transformers, have made significant progress. Large-scale pre-trained diffusion models, which are rich in real-wo…

cs.CV2025

VT-LVLM-AR: A Video-Temporal Large Vision-Language Model Adapter for Fine-Grained Action Recognition in Long-Term Videos

Kaining Li, Shuwei He, Zihan Xu

Human action recognition in long-term videos, characterized by complex backgrounds and subtle action differences, poses significant challenges for traditional deep learning models…

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