4 papers
Intrinsic Gradient Suppression for Label-Noise Prompt Tuning in Vision-Language Models
Jiayu Li, Jiaxin Qi, Sheng Zhou +2
Contrastive vision-language models like CLIP exhibit remarkable zero-shot generalization. However, prompt tuning remains highly sensitive to label noise, as mislabeled samples gene…
Self-Guided Process Reward Optimization with Redefined Step-wise Advantage for Process Reinforcement Learning
Wu Fei, Shuxian Liang, Yibo Yang +5
Process Reinforcement Learning~(PRL) has demonstrated considerable potential in enhancing the reasoning capabilities of Large Language Models~(LLMs). However, introducing additiona…
Efficient Token Compression for Vision Transformer with Spatial Information Preserved
Junzhu Mao, Yang Shen, Jinyang Guo +2
Token compression is essential for reducing the computational and memory requirements of transformer models, enabling their deployment in resource-constrained environments. In this…
Semi-supervised Semantic Segmentation with Multi-Constraint Consistency Learning
Jianjian Yin, Tao Chen, Gensheng Pei +3
Consistency regularization has prevailed in semi-supervised semantic segmentation and achieved promising performance. However, existing methods typically concentrate on enhancing t…