19 citations · 46 across the 13 of their papers we have counts for
5 papers · 1 filter
ContextRL: Enhancing MLLM's Knowledge Discovery Efficiency with Context-Augmented RL
Xingyu Lu, Jinpeng Wang, YiFan Zhang +12
We propose ContextRL, a novel framework that leverages context augmentation to overcome these bottlenecks. Specifically, to enhance Identifiability, we provide the reward model wit…
Continual Learning for Generative AI: From LLMs to MLLMs and Beyond
Haiyang Guo, Fanhu Zeng, Fei Zhu +9
The rapid advancement of generative models has empowered modern AI systems to comprehend and produce highly sophisticated content, even achieving human-level performance in specifi…
ProtoGCD: Unified and Unbiased Prototype Learning for Generalized Category Discovery
Shijie Ma, Fei Zhu, Xu-Yao Zhang +1
Generalized category discovery (GCD) is a pragmatic but underexplored problem, which requires models to automatically cluster and discover novel categories by leveraging the labele…
Open-world machine learning: A review and new outlooks
Fei Zhu, Shijie Ma, Zhen Cheng +4
Machine learning has achieved remarkable success in many applications. However, existing studies are largely based on the closed-world assumption, which assumes that the environmen…
Towards Trustworthy Dataset Distillation
Shijie Ma, Fei Zhu, Zhen Cheng +1
Efficiency and trustworthiness are two eternal pursuits when applying deep learning in real-world applications. With regard to efficiency, dataset distillation (DD) endeavors to re…