9 papers
TADS: Task-Aware Data Selection for Multi-Task Multimodal Pre-Training
Guanjie Cheng, Boyi Li, Lingyu Sun +4
Large-scale multimodal pre-trained models like CLIP rely heavily on high-quality training data, yet raw web-crawled datasets are often noisy, misaligned, and redundant, leading to…
Adaptive Dual-Weighting Framework for Federated Learning via Out-of-Distribution Detection
Zhiwei Ling, Hailiang Zhao, Chao Zhang +8
Federated Learning (FL) enables collaborative model training across large-scale distributed service nodes while preserving data privacy, making it a cornerstone of intelligent serv…
Can Vision-Language Models Handle Long-Context Code? An Empirical Study on Visual Compression
Jianping Zhong, Guochang Li, Chen Zhi +6
Large Language Models (LLMs) struggle with long-context code due to window limitations. Existing textual code compression methods mitigate this via selective filtering but often di…
Video-QTR: Query-Driven Temporal Reasoning Framework for Lightweight Video Understanding
Xinkui Zhao, Zuxin Wang, Yifan Zhang +6
The rapid development of multimodal large-language models (MLLMs) has significantly expanded the scope of visual language reasoning, enabling unified systems to interpret and descr…
TenonOS: A Self-Generating LibOS-on-LibOS Framework for Time-Critical Embedded Operating Systems
Xinkui Zhao, Yifan Zhang, Haidan Zhao +7
The growing complexity of embedded systems creates tension between rich functionality and strict resource and real-time constraints. Traditional monolithic operating system and hyp…
Completion by Comprehension: Guiding Code Generation with Multi-Granularity Understanding
Xinkui Zhao, Rongkai Liu, Yifan Zhang +6
As code completion task from function-level to repository-level, leveraging contextual information from large-scale codebases becomes a core challenge. However, existing retrieval-…