2 citations · 10 across the 23 of their papers we have counts for
12 papers · 1 filter
Fast and Slow Gradient Approximation for Binary Neural Network Optimization
Xinquan Chen, Junqi Gao, Biqing Qi +4
Binary Neural Networks (BNNs) have garnered significant attention due to their immense potential for deployment on edge devices. However, the non-differentiability of the quantizat…
Evolution of Thought: Diverse and High-Quality Reasoning via Multi-Objective Optimization
Biqing Qi, Zhouyi Qian, Yiang Luo +4
As multi-modal large language models (MLLMs) are increasingly applied to complex reasoning tasks, the diversity and quality of reasoning paths become crucial factors affecting thei…
An Efficient Memory Module for Graph Few-Shot Class-Incremental Learning
Dong Li, Aijia Zhang, Junqi Gao +1
Incremental graph learning has gained significant attention for its ability to address the catastrophic forgetting problem in graph representation learning. However, traditional me…
SR-CIS: Self-Reflective Incremental System with Decoupled Memory and Reasoning
Biqing Qi, Junqi Gao, Xinquan Chen +3
The ability of humans to rapidly learn new knowledge while retaining old memories poses a significant challenge for current deep learning models. To handle this challenge, we draw…
Perturbation Towards Easy Samples Improves Targeted Adversarial Transferability
Junqi Gao, Biqing Qi, Yao Li +4
The transferability of adversarial perturbations provides an effective shortcut for black-box attacks. Targeted perturbations have greater practicality but are more difficult to tr…
Online DPO: Online Direct Preference Optimization with Fast-Slow Chasing
Biqing Qi, Pengfei Li, Fangyuan Li +3
Direct Preference Optimization (DPO) improves the alignment of large language models (LLMs) with human values by training directly on human preference datasets, eliminating the nee…
Enhancing Adversarial Transferability via Information Bottleneck Constraints
Biqing Qi, Junqi Gao, Jianxing Liu +2
From the perspective of information bottleneck (IB) theory, we propose a novel framework for performing black-box transferable adversarial attacks named IBTA, which leverages advan…
SMR: State Memory Replay for Long Sequence Modeling
Biqing Qi, Junqi Gao, Kaiyan Zhang +4
Despite the promising performance of state space models (SSMs) in long sequence modeling, limitations still exist. Advanced SSMs like S5 and S6 (Mamba) in addressing non-uniform sa…
Exploring Adversarial Robustness of Deep State Space Models
Biqing Qi, Yang Luo, Junqi Gao +4
Deep State Space Models (SSMs) have proven effective in numerous task scenarios but face significant security challenges due to Adversarial Perturbations (APs) in real-world deploy…
Interactive Continual Learning: Fast and Slow Thinking
Biqing Qi, Xingquan Chen, Junqi Gao +4
Advanced life forms, sustained by the synergistic interaction of neural cognitive mechanisms, continually acquire and transfer knowledge throughout their lifespan. In contrast, con…
Contrastive Augmented Graph2Graph Memory Interaction for Few Shot Continual Learning
Biqing Qi, Junqi Gao, Xingquan Chen +4
Few-Shot Class-Incremental Learning (FSCIL) has gained considerable attention in recent years for its pivotal role in addressing continuously arriving classes. However, it encounte…
Investigating Deep Watermark Security: An Adversarial Transferability Perspective
Biqing Qi, Junqi Gao, Yiang Luo +3
The rise of generative neural networks has triggered an increased demand for intellectual property (IP) protection in generated content. Deep watermarking techniques, recognized fo…