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researcher

Meng Fang

4 papers here

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

author position
  • middle author4

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

fields
  • cs.CL2
  • cs.CV1
  • cs.MM1
ORCID 0000-0001-6745-286X
same name
  • Meng Fang — 11 papers
  • Meng Fang — 11 papers
  • Meng Fang — 9 papers
  • Meng Fang — 3 papers, h 14
  • Meng Fang — 2 papers, h 11
  • Meng Fang — 1 paper, h 7

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
20222024
most citedLearning Granularity-Unified Representations for Text-to-Image Person Re-identification

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

collaborators

4 papers

cs.CL2024

Enhancing Temporal Sensitivity and Reasoning for Time-Sensitive Question Answering

Wanqi Yang, Yanda Li, Meng Fang +1

Time-Sensitive Question Answering (TSQA) demands the effective utilization of specific temporal contexts, encompassing multiple time-evolving facts, to address time-sensitive quest…

cs.CL2023★ 2 cited

How Do Large Language Models Capture the Ever-changing World Knowledge? A Review of Recent Advances

Zihan Zhang, Meng Fang, Ling Chen +2

Although large language models (LLMs) are impressive in solving various tasks, they can quickly be outdated after deployment. Maintaining their up-to-date status is a pressing conc…

cs.CV2022★ 9 cited

Learning Granularity-Unified Representations for Text-to-Image Person Re-identification

Zhiyin Shao, Xinyu Zhang, Meng Fang +3

Text-to-image person re-identification (ReID) aims to search for pedestrian images of an interested identity via textual descriptions. It is challenging due to both rich intra-moda…

cs.MM2022

Dynamic Contrastive Distillation for Image-Text Retrieval

Jun Rao, Liang Ding, Shuhan Qi +4

Although the vision-and-language pretraining (VLP) equipped cross-modal image-text retrieval (ITR) has achieved remarkable progress in the past two years, it suffers from a major d…

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