5 papers
COOPER: A Unified Model for Cooperative Perception and Reasoning in Spatial Intelligence
Zefeng Zhang, Xiangzhao Hao, Hengzhu Tang +8
Visual Spatial Reasoning is crucial for enabling Multimodal Large Language Models (MLLMs) to understand object properties and spatial relationships, yet current models still strugg…
Leveraging Generative Models for Real-Time Query-Driven Text Summarization in Large-Scale Web Search
Zeyu Xiong, Yixuan Nan, Li Gao +4
In the dynamic landscape of large-scale web search, Query-Driven Text Summarization (QDTS) aims to generate concise and informative summaries from textual documents based on a give…
Debiasing Multimodal Large Language Models via Noise-Aware Preference Optimization
Zefeng Zhang, Hengzhu Tang, Jiawei Sheng +6
Multimodal Large Language Models excel in various tasks, yet often struggle with modality bias, where the model tends to rely heavily on a single modality and overlook critical inf…
Multi-Branch Collaborative Learning Network for Video Quality Assessment in Industrial Video Search
Hengzhu Tang, Zefeng Zhang, Zhiping Li +5
Video Quality Assessment (VQA) is vital for large-scale video retrieval systems, aimed at identifying quality issues to prioritize high-quality videos. In industrial systems, low-q…
Exploring Preference-Guided Diffusion Model for Cross-Domain Recommendation
Xiaodong Li, Hengzhu Tang, Jiawei Sheng +5
Cross-domain recommendation (CDR) has been proven as a promising way to alleviate the cold-start issue, in which the most critical problem is how to draw an informative user repres…