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Chang Gao

13 papers hereh-index 78.2k citations15 works total

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

author position
  • first author1
  • middle author9

Across the 10 of 13 papers where every author was matched, so the position is known.

fields
  • cs.CL4
  • cs.CV4
  • cs.LG3
  • cs.AI1
  • cs.CR1
same name
  • Chang Gao — 10 papers, h 4
  • Chang Gao — 9 papers, h 5
  • Chang Gao — 6 papers, h 14
  • Chang Gao — 6 papers, h 7
  • Chang Gao — 4 papers, h 2
  • Chang Gao — 4 papers, h 5

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 citedQwen3 Technical Report

111 citations · 128 across the 12 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2026

HopChain: Multi-Hop Data Synthesis for Generalizable Vision-Language Reasoning

Shenzhi Wang, Shixuan Liu, Jing Zhou +8

Vision-language models (VLMs) show strong multimodal capabilities but still struggle with fine-grained vision-language reasoning. We find that long chain-of-thought (CoT) reasoning…

cs.CV2026

UI-Venus-1.5 Technical Report

Venus Team, Changlong Gao, Zhangxuan Gu +24

GUI agents have emerged as a powerful paradigm for automating interactions in digital environments, yet achieving both broad generality and consistently strong task performance rem…

cs.CV2025★ 16 cited

Qwen3-VL Technical Report

Shuai Bai, Yuxuan Cai, Ruizhe Chen +61

We introduce Qwen3-VL, the most capable vision-language model in the Qwen series to date, achieving superior performance across a broad range of multimodal benchmarks. It natively…

cs.CV2025★ 1 cited

UI-Venus Technical Report: Building High-performance UI Agents with RFT

Zhangxuan Gu, Zhengwen Zeng, Zhenyu Xu +21

We present UI-Venus, a native UI agent that takes only screenshots as input based on a multimodal large language model. UI-Venus achieves SOTA performance on both UI grounding and…

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