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Chenghao Zhang

3 papers here

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

author position
  • first author1
  • middle author2

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • cs.CL1
ORCID 0000-0001-6515-1633
same name
  • Chenghao Zhang — 1 paper, h 2
  • Chenghao Zhang — 1 paper
  • Chenghao Zhang — 1 paper
  • Chenghao Zhang — 1 paper
  • Chenghao Zhang — 1 paper
  • Chenghao Zhang — 1 paper

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 citedAddressCLIP: Empowering Vision-Language Models for City-wide Image Address Localization

1 citations · 1 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2025

Re-ranking Reasoning Context with Tree Search Makes Large Vision-Language Models Stronger

Qi Yang, Chenghao Zhang, Lubin Fan +3

Recent advancements in Large Vision Language Models (LVLMs) have significantly improved performance in Visual Question Answering (VQA) tasks through multimodal Retrieval-Augmented…

cs.CL2024

Progressive Multimodal Reasoning via Active Retrieval

Guanting Dong, Chenghao Zhang, Mengjie Deng +3

Multi-step multimodal reasoning tasks pose significant challenges for multimodal large language models (MLLMs), and finding effective ways to enhance their performance in such scen…

cs.CV2024★ 1 cited

AddressCLIP: Empowering Vision-Language Models for City-wide Image Address Localization

Shixiong Xu, Chenghao Zhang, Lubin Fan +3

In this study, we introduce a new problem raised by social media and photojournalism, named Image Address Localization (IAL), which aims to predict the readable textual address whe…

cs.CV2024

Reusable Architecture Growth for Continual Stereo Matching

Chenghao Zhang, Gaofeng Meng, Bin Fan +4

The remarkable performance of recent stereo depth estimation models benefits from the successful use of convolutional neural networks to regress dense disparity. Akin to most tasks…

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