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researcher

Ming Cheng

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.CV3
  • cs.SD1
same name
  • Ming Cheng — 6 papers
  • Ming Cheng — 5 papers
  • Ming Cheng — 5 papers
  • Ming Cheng — 4 papers
  • Ming Cheng — 4 papers
  • Ming Cheng — 3 papers, h 5

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 citedLearning Musical Representations for Music Performance Question Answering

1 citations · 1 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2025

ProtoVQA: An Adaptable Prototypical Framework for Explainable Fine-Grained Visual Question Answering

Xingjian Diao, Weiyi Wu, Keyi Kong +5

Visual Question Answering (VQA) is increasingly used in diverse applications ranging from general visual reasoning to safety-critical domains such as medical imaging and autonomous…

cs.SD2025

Learning Sparsity for Effective and Efficient Music Performance Question Answering

Xingjian Diao, Tianzhen Yang, Chunhui Zhang +3

Music performances, characterized by dense and continuous audio as well as seamless audio-visual integration, present unique challenges for multimodal scene understanding and reaso…

cs.CV2025★ 1 cited

Learning Musical Representations for Music Performance Question Answering

Xingjian Diao, Chunhui Zhang, Tingxuan Wu +4

Music performances are representative scenarios for audio-visual modeling. Unlike common scenarios with sparse audio, music performances continuously involve dense audio signals th…

cs.CV2025

Temporal Working Memory: Query-Guided Segment Refinement for Enhanced Multimodal Understanding

Xingjian Diao, Chunhui Zhang, Weiyi Wu +5

Multimodal foundation models (MFMs) have demonstrated significant success in tasks such as visual captioning, question answering, and image-text retrieval. However, these models fa…

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