12 papers
AIM-Bench: Benchmarking and Improving Affective Image Manipulation via Fine-Grained Hierarchical Control
Shi Chen, Xuecheng Wu, Heli Sun +8
Affective Image Manipulation (AIM) aims to evoke specific emotions through targeted editing. Current image editing benchmarks primarily focus on object-level modifications in gener…
FED-Bench: A Cross-Granular Benchmark for Disentangled Evaluation of Facial Expression Editing
Fengjian Xue, Xuecheng Wu, Heli Sun +8
Facial expression image editing requires fine-grained control to strictly preserve human identity and background while precisely manipulating expression. However, existing editing…
Diffusion Probe: Generated Image Result Prediction Using CNN Probes
Benlei Cui, Bukun Huang, Zhizeng Ye +7
Text-to-image (T2I) diffusion models lack an efficient mechanism for early quality assessment, leading to costly trial-and-error in multi-generation scenarios such as prompt iterat…
TextPecker: Rewarding Structural Anomaly Quantification for Enhancing Visual Text Rendering
Hanshen Zhu, Yuliang Liu, Xuecheng Wu +7
Visual Text Rendering (VTR) remains a critical challenge in text-to-image generation, where even advanced models frequently produce text with structural anomalies such as distortio…
AdaLRS: Loss-Guided Adaptive Learning Rate Search for Efficient Foundation Model Pretraining
Hongyuan Dong, Dingkang Yang, Xiao Liang +2
Learning rate is widely regarded as crucial for effective foundation model pretraining. Recent research explores and demonstrates the transferability of learning rate configuration…
MEML-GRPO: Heterogeneous Multi-Expert Mutual Learning for RLVR Advancement
Weitao Jia, Jinghui Lu, Haiyang Yu +17
Recent advances demonstrate that reinforcement learning with verifiable rewards (RLVR) significantly enhances the reasoning capabilities of large language models (LLMs). However, s…