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researcher

Meishan Zhang

9 papers hereh-index 4294 citations13 works total

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

author position
  • middle author9

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

fields
  • cs.CL3
  • cs.CV3
  • cs.AI1
  • cs.CY1
  • cs.MM1
same name
  • Meishan Zhang — 30 papers, h 12
  • Meishan Zhang — 27 papers, h 19
  • Meishan Zhang — 17 papers, h 30
  • Meishan Zhang — 4 papers, h 2
  • Meishan Zhang — 2 papers
  • Meishan Zhang — 2 papers, h 3

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 citedEnhancing Video-Language Representations with Structural Spatio-Temporal Alignment

63 citations · 66 across the 9 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.CV2024

Synergistic Dual Spatial-aware Generation of Image-to-Text and Text-to-Image

Yu Zhao, Hao Fei, Xiangtai Li +6

In the visual spatial understanding (VSU) area, spatial image-to-text (SI2T) and spatial text-to-image (ST2I) are two fundamental tasks that appear in dual form. Existing methods f…

cs.CL2024

Grammar Induction from Visual, Speech and Text

Yu Zhao, Hao Fei, Shengqiong Wu +3

Grammar Induction could benefit from rich heterogeneous signals, such as text, vision, and acoustics. In the process, features from distinct modalities essentially serve complement…

cs.MM2024

SpeechEE: A Novel Benchmark for Speech Event Extraction

Bin Wang, Meishan Zhang, Hao Fei +5

Event extraction (EE) is a critical direction in the field of information extraction, laying an important foundation for the construction of structured knowledge bases. EE from tex…

cs.CV2024★ 63 cited

Enhancing Video-Language Representations with Structural Spatio-Temporal Alignment

Hao Fei, Shengqiong Wu, Meishan Zhang +3

While pre-training large-scale video-language models (VLMs) has shown remarkable potential for various downstream video-language tasks, existing VLMs can still suffer from certain…

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