6 papers
Visual Search Augmented Chain-of-Thought Reasoning for Attribute Value Extraction from Product Videos
Tong Wu, Ming Cheng, Jiazhen Hu +2
Existing approaches to visual attribute value extraction (AVE) primarily rely on static product images, failing to capture temporal cues, multi-angle views and fine-grained visual…
Hierarchical Wasserstein Merging for Multi-Domain Multi-Task Learning: From Specialists to a Generalist
Ming Cheng, Jiaying Gong, Hoda Eldardiry
Multi-domain multi-task learning (MD-MTL) aims to build a single generalist model that performs well across heterogeneous domains and tasks. However, joint training often suffers f…
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…
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…
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…
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…