6 citations · 51 across the 54 of their papers we have counts for
24 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…
Fourier Position Embedding: Enhancing Attention's Periodic Extension for Length Generalization
Ermo Hua, Che Jiang, Xingtai Lv +7
Extending the context length of Language Models (LMs) by improving Rotary Position Embedding (RoPE) has become a trend. While prior works mainly address RoPE's limitations within a…
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…
On the token distance modeling ability of higher RoPE attention dimension
Xiangyu Hong, Che Jiang, Biqing Qi +4
Length extrapolation algorithms based on Rotary position embedding (RoPE) have shown promising results in extending the context length of language models. However, understanding ho…
Many Heads Are Better Than One: Improved Scientific Idea Generation by A LLM-Based Multi-Agent System
Haoyang Su, Renqi Chen, Shixiang Tang +10
The rapid advancement of scientific progress requires innovative tools that can accelerate knowledge discovery. Although recent AI methods, particularly large language models (LLMs…
MSI-Agent: Incorporating Multi-Scale Insight into Embodied Agents for Superior Planning and Decision-Making
Dayuan Fu, Biqing Qi, Yihuai Gao +3
Long-term memory is significant for agents, in which insights play a crucial role. However, the emergence of irrelevant insight and the lack of general insight can greatly undermin…
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…
Neural Residual Diffusion Models for Deep Scalable Vision Generation
Zhiyuan Ma, Liangliang Zhao, Biqing Qi +1
The most advanced diffusion models have recently adopted increasingly deep stacked networks (e.g., U-Net or Transformer) to promote the generative emergence capabilities of vision…
Safe-SD: Safe and Traceable Stable Diffusion with Text Prompt Trigger for Invisible Generative Watermarking
Zhiyuan Ma, Guoli Jia, Biqing Qi +1
Recently, stable diffusion (SD) models have typically flourished in the field of image synthesis and personalized editing, with a range of photorealistic and unprecedented images b…
Large Language Models as Biomedical Hypothesis Generators: A Comprehensive Evaluation
Biqing Qi, Kaiyan Zhang, Kai Tian +6
The rapid growth of biomedical knowledge has outpaced our ability to efficiently extract insights and generate novel hypotheses. Large language models (LLMs) have emerged as a prom…
Towards Building Specialized Generalist AI with System 1 and System 2 Fusion
Kaiyan Zhang, Biqing Qi, Bowen Zhou
In this perspective paper, we introduce the concept of Specialized Generalist Artificial Intelligence (SGAI or simply SGI) as a crucial milestone toward Artificial General Intellig…
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…
Fast and Slow Generating: An Empirical Study on Large and Small Language Models Collaborative Decoding
Kaiyan Zhang, Jianyu Wang, Ning Ding +4
Large Language Models (LLMs) exhibit impressive capabilities across various applications but encounter substantial challenges such as high inference latency, considerable training…
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…
UltraMedical: Building Specialized Generalists in Biomedicine
Kaiyan Zhang, Sihang Zeng, Ermo Hua +11
Large Language Models (LLMs) have demonstrated remarkable capabilities across various domains and are moving towards more specialized areas. Recent advanced proprietary models such…
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…
On Large Language Models' Hallucination with Regard to Known Facts
Che Jiang, Biqing Qi, Xiangyu Hong +6
Large language models are successful in answering factoid questions but are also prone to hallucination. We investigate the phenomenon of LLMs possessing correct answer knowledge y…
CoGenesis: A Framework Collaborating Large and Small Language Models for Secure Context-Aware Instruction Following
Kaiyan Zhang, Jianyu Wang, Ermo Hua +3
With the advancement of language models (LMs), their exposure to private data is increasingly inevitable, and their deployment (especially for smaller ones) on personal devices, su…
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…