9 citations · 13 across the 7 of their papers we have counts for
Showing 2024Show all
3 papers · 1 filter
cs.CV2024★ 1 cited
Advancing Multimodal Large Language Models in Chart Question Answering with Visualization-Referenced Instruction Tuning
Xingchen Zeng, Haichuan Lin, Yilin Ye +1
Emerging multimodal large language models (MLLMs) exhibit great potential for chart question answering (CQA). Recent efforts primarily focus on scaling up training datasets (i.e.,…
cs.CV2024★ 1 cited
ModalChorus: Visual Probing and Alignment of Multi-modal Embeddings via Modal Fusion Map
Yilin Ye, Shishi Xiao, Xingchen Zeng +1
Multi-modal embeddings form the foundation for vision-language models, such as CLIP embeddings, the most widely used text-image embeddings. However, these embeddings are vulnerable…
cs.HC2024★ 2 cited
IntentTuner: An Interactive Framework for Integrating Human Intents in Fine-tuning Text-to-Image Generative Models
Xingchen Zeng, Ziyao Gao, Yilin Ye +1
Fine-tuning facilitates the adaptation of text-to-image generative models to novel concepts (e.g., styles and portraits), empowering users to forge creatively customized content. R…