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Zhicheng Dou

120 papers hereh-index 283k citations168 works total

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

author position
  • first author1
  • middle author39
  • last author75

Across the 115 of 120 papers where every author was matched, so the position is known.

fields
  • cs.CL46
  • cs.AI32
  • cs.IR30
  • cs.LG6
  • cs.CV4
  • cs.CR1
same name
  • Zhicheng Dou — 56 papers, h 42
  • Zhicheng Dou — 3 papers
  • Zhicheng Dou — 1 paper
  • Zhicheng Dou — 1 paper
  • Zhicheng Dou — 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

activity
20212026
most citedA Multi-Task Embedder For Retrieval Augmented LLMs

18 citations · 135 across the 104 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2026

DeepImageSearch: Benchmarking Multimodal Agents for Context-Aware Image Retrieval in Visual Histories

Chenlong Deng, Mengjie Deng, Junjie Wu +10

Existing multimodal retrieval systems excel at semantic matching but implicitly assume that query-image relevance can be measured in isolation. This paradigm overlooks the rich dep…

cs.CV2025

MoCa: Modality-aware Continual Pre-training Makes Better Bidirectional Multimodal Embeddings

Haonan Chen, Hong Liu, Yuping Luo +4

Multimodal embedding models, built upon causal Vision Language Models (VLMs), have shown promise in various tasks. However, current approaches face three key limitations: the use o…

cs.CV2025

Memory-enhanced Retrieval Augmentation for Long Video Understanding

Huaying Yuan, Zheng Liu, Minghao Qin +5

Efficient long-video understanding~(LVU) remains a challenging task in computer vision. Current long-context vision-language models~(LVLMs) suffer from information loss due to comp…

cs.CV2025

mmE5: Improving Multimodal Multilingual Embeddings via High-quality Synthetic Data

Haonan Chen, Liang Wang, Nan Yang +4

Multimodal embedding models have gained significant attention for their ability to map data from different modalities, such as text and images, into a unified representation space.…

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