4 citations · 5 across the 4 of their papers we have counts for
6 papers · 1 filter
ChatABL: Abductive Learning via Natural Language Interaction with ChatGPT
Tianyang Zhong, Yaonai Wei, Li Yang +13
Large language models (LLMs) such as ChatGPT have recently demonstrated significant potential in mathematical abilities, providing valuable reasoning paradigm consistent with human…
Model Extraction Attacks on Split Federated Learning
Jingtao Li, Adnan Siraj Rakin, Xing Chen +4
Federated Learning (FL) is a popular collaborative learning scheme involving multiple clients and a server. FL focuses on protecting clients' data but turns out to be highly vulner…
Efficient Self-supervised Continual Learning with Progressive Task-correlated Layer Freezing
Li Yang, Sen Lin, Fan Zhang +2
Inspired by the success of Self-supervised learning (SSL) in learning visual representations from unlabeled data, a few recent works have studied SSL in the context of continual le…
Automating Method Naming with Context-Aware Prompt-Tuning
Jie Zhu, Lingwei Li, Li Yang +2
Method names are crucial to program comprehension and maintenance. Recently, many approaches have been proposed to automatically recommend method names and detect inconsistent name…
Active Learning in Brain Tumor Segmentation with Uncertainty Sampling, Annotation Redundancy Restriction, and Data Initialization
Daniel D Kim, Rajat S Chandra, Jian Peng +14
Deep learning models have demonstrated great potential in medical 3D imaging, but their development is limited by the expensive, large volume of annotated data required. Active lea…
Feasibility Analysis of Grover-meets-Simon Algorithm
Qianru Zhu, Huiqin Xie, Qiqing Xia +1
Quantum algorithm is a key tool for cryptanalysis. At present, people are committed to building powerful quantum algorithms and tapping the potential of quantum algorithms, so as t…