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Zhaoxiang Zhang

4 papers hereh-index 5166 citations6 works total

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

author position
  • middle author2
  • last author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • cs.IR1
  • cs.SE1
same name
  • Zhaoxiang Zhang — 59 papers, h 60
  • Zhaoxiang Zhang — 27 papers, h 13
  • Zhaoxiang Zhang — 23 papers, h 14
  • Zhaoxiang Zhang — 17 papers, h 8
  • Zhaoxiang Zhang — 13 papers, h 8
  • Zhaoxiang Zhang — 11 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

most citedSheetCopilot: Bringing Software Productivity to the Next Level through Large Language Models

6 citations · 11 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2025

AutoGUI: Scaling GUI Grounding with Automatic Functionality Annotations from LLMs

Hongxin Li, Jingfan Chen, Jingran Su +3

User interface understanding with vision-language models (VLMs) has received much attention due to its potential for enhancing software automation. However, existing datasets used…

cs.CV2023★ 3 cited

DiffusePast: Diffusion-based Generative Replay for Class Incremental Semantic Segmentation

Jingfan Chen, Yuxi Wang, Pengfei Wang +4

The Class Incremental Semantic Segmentation (CISS) extends the traditional segmentation task by incrementally learning newly added classes. Previous work has introduced generative…

cs.SE2023★ 6 cited

SheetCopilot: Bringing Software Productivity to the Next Level through Large Language Models

Hongxin Li, Jingran Su, Yuntao Chen +2

Computer end users have spent billions of hours completing daily tasks like tabular data processing and project timeline scheduling. Most of these tasks are repetitive and error-pr…

cs.IR2023★ 2 cited

Fairly Adaptive Negative Sampling for Recommendations

Xiao Chen, Wenqi Fan, Jingfan Chen +4

Pairwise learning strategies are prevalent for optimizing recommendation models on implicit feedback data, which usually learns user preference by discriminating between positive (…

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