4 papers
Beyond Words and Pixels: A Benchmark for Implicit World Knowledge Reasoning in Generative Models
Tianyang Han, Junhao Su, Junjie Hu +4
Text-to-image (T2I) models today are capable of producing photorealistic, instruction-following images, yet they still frequently fail on prompts that require implicit world knowle…
LayoutCoT: Unleashing the Deep Reasoning Potential of Large Language Models for Layout Generation
Hengyu Shi, Junhao Su, Tianyang Han +2
Conditional layout generation aims to automatically generate visually appealing and semantically coherent layouts from user-defined constraints. While recent methods based on gener…
Faster Multi-GPU Training with PPLL: A Pipeline Parallelism Framework Leveraging Local Learning
Xiuyuan Guo, Chengqi Xu, Guinan Guo +6
Currently, training large-scale deep learning models is typically achieved through parallel training across multiple GPUs. However, due to the inherent communication overhead and s…
Replacement Learning: Training Vision Tasks with Fewer Learnable Parameters
Yuming Zhang, Peizhe Wang, Shouxin Zhang +3
Traditional end-to-end deep learning models often enhance feature representation and overall performance by increasing the depth and complexity of the network during training. Howe…