29 citations · 35 across the 7 of their papers we have counts for
7 papers
Food-500 Cap: A Fine-Grained Food Caption Benchmark for Evaluating Vision-Language Models
Zheng Ma, Mianzhi Pan, Wenhan Wu +4
Vision-language models (VLMs) have shown impressive performance in substantial downstream multi-modal tasks. However, only comparing the fine-tuned performance on downstream tasks…
ADS-Cap: A Framework for Accurate and Diverse Stylized Captioning with Unpaired Stylistic Corpora
Kanzhi Cheng, Zheng Ma, Shi Zong +3
Generating visually grounded image captions with specific linguistic styles using unpaired stylistic corpora is a challenging task, especially since we expect stylized captions wit…
Beyond Generic: Enhancing Image Captioning with Real-World Knowledge using Vision-Language Pre-Training Model
Kanzhi Cheng, Wenpo Song, Zheng Ma +3
Current captioning approaches tend to generate correct but "generic" descriptions that lack real-world knowledge, e.g., named entities and contextual information. Considering that…
Probing Cross-modal Semantics Alignment Capability from the Textual Perspective
Zheng Ma, Shi Zong, Mianzhi Pan +4
In recent years, vision and language pre-training (VLP) models have advanced the state-of-the-art results in a variety of cross-modal downstream tasks. Aligning cross-modal semanti…
Music-to-Text Synaesthesia: Generating Descriptive Text from Music Recordings
Zhihuan Kuang, Shi Zong, Jianbing Zhang +2
In this paper, we consider a novel research problem: music-to-text synaesthesia. Different from the classical music tagging problem that classifies a music recording into pre-defin…
Learning Representation Mapping for Relation Detection in Knowledge Base Question Answering
Peng Wu, Shujian Huang, Rongxiang Weng +4
Relation detection is a core step in many natural language process applications including knowledge base question answering. Previous efforts show that single-fact questions could…
Topic2Vec: Learning Distributed Representations of Topics
Li-Qiang Niu, Xin-Yu Dai
Latent Dirichlet Allocation (LDA) mining thematic structure of documents plays an important role in nature language processing and machine learning areas. However, the probability…