720 citations · 810 across the 30 of their papers we have counts for
30 papers
Learning While Acting: A Skill-Enhanced Test-Time Co-Evolution Framework for Online Lifelong Learning Agents
Bo Mao, Jie Zhou, Yutao Yang +5
Lifelong learning is essential for Large Language Model (LLM) agents operating in dynamic, interactive environments. However, existing lifelong learning agents for long-horizon tas…
Dynamic Multimodal Activation Steering for Hallucination Mitigation in Large Vision-Language Models
Jianghao Yin, Qin Chen, Kedi Chen +3
Large Vision-Language Models (LVLMs) exhibit outstanding performance on vision-language tasks but struggle with hallucination problems. Through in-depth analysis of LVLM activation…
Mitigating Strategy Preference Bias in Emotional Support Conversation via Uncertainty Estimations
Yougen Zhou, Qin Chen, Ningning Zhou +3
Emotional support conversation (ESC) aims to alleviate distress through empathetic dialogue, yet large language models (LLMs) face persistent challenges in delivering effective ESC…
Forget What's Sensitive, Remember What Matters: Token-Level Differential Privacy in Memory Sculpting for Continual Learning
Bihao Zhan, Jie Zhou, Junsong Li +9
Continual Learning (CL) models, while adept at sequential knowledge acquisition, face significant and often overlooked privacy challenges due to accumulating diverse information. T…
RMoA: Optimizing Mixture-of-Agents through Diversity Maximization and Residual Compensation
Zhentao Xie, Chengcheng Han, Jinxin Shi +4
Although multi-agent systems based on large language models show strong capabilities on multiple tasks, they are still limited by high computational overhead, information loss, and…
Task-Core Memory Management and Consolidation for Long-term Continual Learning
Tianyu Huai, Jie Zhou, Yuxuan Cai +5
In this paper, we focus on a long-term continual learning (CL) task, where a model learns sequentially from a stream of vast tasks over time, acquiring new knowledge while retainin…
CL-MoE: Enhancing Multimodal Large Language Model with Dual Momentum Mixture-of-Experts for Continual Visual Question Answering
Tianyu Huai, Jie Zhou, Xingjiao Wu +4
Multimodal large language models (MLLMs) have garnered widespread attention from researchers due to their remarkable understanding and generation capabilities in visual language ta…
Multi-Type Preference Learning: Empowering Preference-Based Reinforcement Learning with Equal Preferences
Ziang Liu, Junjie Xu, Xingjiao Wu +2
Preference-Based reinforcement learning (PBRL) learns directly from the preferences of human teachers regarding agent behaviors without needing meticulously designed reward functio…
MindScope: Exploring cognitive biases in large language models through Multi-Agent Systems
Zhentao Xie, Jiabao Zhao, Yilei Wang +4
Detecting cognitive biases in large language models (LLMs) is a fascinating task that aims to probe the existing cognitive biases within these models. Current methods for detecting…
MultiColor: Image Colorization by Learning from Multiple Color Spaces
Xiangcheng Du, Zhao Zhou, Yanlong Wang +3
Deep networks have shown impressive performance in the image restoration tasks, such as image colorization. However, we find that previous approaches rely on the digital representa…
Fine-Grained Scene Image Classification with Modality-Agnostic Adapter
Yiqun Wang, Zhao Zhou, Xiangcheng Du +3
When dealing with the task of fine-grained scene image classification, most previous works lay much emphasis on global visual features when doing multi-modal feature fusion. In oth…
FairMonitor: A Dual-framework for Detecting Stereotypes and Biases in Large Language Models
Yanhong Bai, Jiabao Zhao, Jinxin Shi +3
Detecting stereotypes and biases in Large Language Models (LLMs) is crucial for enhancing fairness and reducing adverse impacts on individuals or groups when these models are appli…
UMAAF: Unveiling Aesthetics via Multifarious Attributes of Images
Weijie Li, Yitian Wan, Xingjiao Wu +3
With the increasing prevalence of smartphones and websites, Image Aesthetic Assessment (IAA) has become increasingly crucial. While the significance of attributes in IAA is widely…
DCQA: Document-Level Chart Question Answering towards Complex Reasoning and Common-Sense Understanding
Anran Wu, Luwei Xiao, Xingjiao Wu +6
Visually-situated languages such as charts and plots are omnipresent in real-world documents. These graphical depictions are human-readable and are often analyzed in visually-rich…
Progressive Evidence Refinement for Open-domain Multimodal Retrieval Question Answering
Shuwen Yang, Anran Wu, Xingjiao Wu +4
Pre-trained multimodal models have achieved significant success in retrieval-based question answering. However, current multimodal retrieval question-answering models face two main…
CGMI: Configurable General Multi-Agent Interaction Framework
Shi Jinxin, Zhao Jiabao, Wang Yilei +3
Benefiting from the powerful capabilities of large language models (LLMs), agents based on LLMs have shown the potential to address domain-specific tasks and emulate human behavior…
FairMonitor: A Four-Stage Automatic Framework for Detecting Stereotypes and Biases in Large Language Models
Yanhong Bai, Jiabao Zhao, Jinxin Shi +3
Detecting stereotypes and biases in Large Language Models (LLMs) can enhance fairness and reduce adverse impacts on individuals or groups when these LLMs are applied. However, the…
DDT: Dual-branch Deformable Transformer for Image Denoising
Kangliang Liu, Xiangcheng Du, Sijie Liu +3
Transformer is beneficial for image denoising tasks since it can model long-range dependencies to overcome the limitations presented by inductive convolutional biases. However, dir…
LoGoNet: Towards Accurate 3D Object Detection with Local-to-Global Cross-Modal Fusion
Xin Li, Tao Ma, Yuenan Hou +8
LiDAR-camera fusion methods have shown impressive performance in 3D object detection. Recent advanced multi-modal methods mainly perform global fusion, where image features and poi…
Homogeneous Multi-modal Feature Fusion and Interaction for 3D Object Detection
Xin Li, Botian Shi, Yuenan Hou +4
Multi-modal 3D object detection has been an active research topic in autonomous driving. Nevertheless, it is non-trivial to explore the cross-modal feature fusion between sparse 3D…
Progressive Scene Text Erasing with Self-Supervision
Xiangcheng Du, Zhao Zhou, Yingbin Zheng +3
Scene text erasing seeks to erase text contents from scene images and current state-of-the-art text erasing models are trained on large-scale synthetic data. Although data syntheti…
Multi-channel Attentive Graph Convolutional Network With Sentiment Fusion For Multimodal Sentiment Analysis
Luwei Xiao, Xingjiao Wu, Wen Wu +2
Nowadays, with the explosive growth of multimodal reviews on social media platforms, multimodal sentiment analysis has recently gained popularity because of its high relevance to t…
Cross-Domain Document Layout Analysis Using Document Style Guide
Xingjiao Wu, Luwei Xiao, Xiangcheng Du +5
The document layout analysis (DLA) aims to decompose document images into high-level semantic areas (i.e., figures, tables, texts, and background). Creating a DLA framework with st…
Document Layout Analysis with Aesthetic-Guided Image Augmentation
Tianlong Ma, Xingjiao Wu, Xin Li +4
Document layout analysis (DLA) plays an important role in information extraction and document understanding. At present, document layout analysis has reached a milestone achievemen…