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Ming Cheng

4 papers hereh-index 210 citations6 works total

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

author position
  • first author3
  • middle author1

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

fields
  • cs.CL2
  • cs.CV1
  • cs.IR1
same name
  • Ming Cheng — 8 papers, h 11
  • Ming Cheng — 6 papers, h 8
  • Ming Cheng — 4 papers, h 1
  • Ming Cheng — 3 papers, h 2
  • Ming Cheng — 3 papers, h 2
  • Ming Cheng — 1 paper, h 0

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

collaborators

4 papers

cs.CV2025

VideoAVE: A Multi-Attribute Video-to-Text Attribute Value Extraction Dataset and Benchmark Models

Ming Cheng, Tong Wu, Jiazhen Hu +2

Attribute Value Extraction (AVE) is important for structuring product information in e-commerce. However, existing AVE datasets are primarily limited to text-to-text or image-to-te…

cs.CL2025

Sci-LoRA: Mixture of Scientific LoRAs for Cross-Domain Lay Paraphrasing

Ming Cheng, Jiaying Gong, Hoda Eldardiry

Lay paraphrasing aims to make scientific information accessible to audiences without technical backgrounds. However, most existing studies focus on a single domain, such as biomedi…

cs.IR2025

Visual Zero-Shot E-Commerce Product Attribute Value Extraction

Jiaying Gong, Ming Cheng, Hongda Shen +3

Existing zero-shot product attribute value (aspect) extraction approaches in e-Commerce industry rely on uni-modal or multi-modal models, where the sellers are asked to provide det…

cs.CL2025

VTechAGP: An Academic-to-General-Audience Text Paraphrase Dataset and Benchmark Models

Ming Cheng, Jiaying Gong, Chenhan Yuan +3

Existing text simplification or paraphrase datasets mainly focus on sentence-level text generation in a general domain. These datasets are typically developed without using domain…

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