1 citations · 1 across the 4 of their papers we have counts for
4 papers
Quantum Incremental Learning with Mixed State Prototypes
Yu Wu, Qianli Zhou, Xinyang Deng +3
Incremental learning models are required to learn new classes sequentially without catastrophic forgetting, while operating under parameter and memory constraints. In the Noisy Int…
DOW-KE: Anchor-Free Multi-Layer Knowledge Editing via Direct End-to-End Weight Optimization
Ran Chen, Junbo Zhang, Qianli Zhou +2
Multi-layer locate-then-edit methods for knowledge editing first optimize target residual-stream activations (anchors) at selected layers, then realize them layer by layer as weigh…
DataRx: Missingness-Aware Sampling for Safer Large Language Model Task-Specific Fine-Tuning
Junbo Zhang, Qianli Zhou, Xinyang Deng +1
Task-specific fine-tuning can improve the performance of large language models (LLMs) on downstream tasks. However, our study reveals that task-specific fine-tuning can also weaken…
Feature Entanglement-based Quantum Multimodal Fusion Neural Network
Yu Wu, Qianli Zhou, Jie Geng +2
Multimodal learning aims to enhance perceptual and decision-making capabilities by integrating information from diverse sources. However, classical deep learning approaches face a…