6 citations · 9 across the 14 of their papers we have counts for
16 papers
OPSRD: On-Policy Self-Role Distillation
Weijie Ren, Yanwen Zhang, Hao Li +3
Role prompting elicits specialized behavior from large language models through an expert identity, offering a lightweight way to guide reasoning on demanding tasks. However, evalua…
SEPAL: Separated Expert Pairs with Answer-Level Fusion for Reliable LLM Collaboration
Weijie Ren, Yanwen Zhang, Hao Li +3
Multi-agent collaboration lets large language models (LLMs) improve question answering through deliberation and feedback. Yet shared discussion couples correction with exposure to…
ViSAGE: Constructing Self-Correcting Memories for Long-Form Video Understanding
Xinkui Zhao, Enbo Chen, Yifan Zhang +4
Multimodal agents operating in long-horizon environments must build and continually update multimedia memories to support entity-consistent, temporally grounded reasoning. However,…
ATOM: Instantiating Budget-Controllable Multi-Agent Collaboration via Nucleus-Electron Hierarchy
Xinkui Zhao, Sai Liu, Yifan Zhang +6
Large Language Model (LLM)-based multi-agent systems rely on optimized collaboration topologies to balance performance and communication costs. However, current methods struggle wi…
ProMAS: Proactive Error Forecasting for Multi-Agent Systems Using Markov Transition Dynamics
Xinkui Zhao, Sai Liu, Yifan Zhang +4
The integration of Large Language Models into Multi-Agent Systems (MAS) has enabled the so-lution of complex, long-horizon tasks through collaborative reasoning. However, this coll…
Video-QTR: Query-Driven Temporal Reasoning Framework for Lightweight Video Understanding
Xinkui Zhao, Zuxin Wang, Yifan Zhang +6
The rapid development of multimodal large-language models (MLLMs) has significantly expanded the scope of visual language reasoning, enabling unified systems to interpret and descr…
MUSE: A Heterogeneity-Aware Multimedia Search Engine for Mobile SoCs
Xinkui Zhao, Qingyu Ma, Yifan Zhang +6
On-device multimedia retrieval is vital for smartphones, enabling applications like cross-modal semantic search and multimodal personal AI agents. However, realizing efficient retr…
RIPRAG: Hack a Black-box Retrieval-Augmented Generation Question-Answering System with Reinforcement Learning
Meng Xi, Sihan Lv, Yechen Jin +4
Retrieval-Augmented Generation (RAG) systems based on Large Language Models (LLMs) have become a core technology for tasks such as question-answering (QA) and content generation. R…
DRAMA: Next-Gen Dynamic Orchestration for Resilient Multi-Agent Ecosystems in Flux
Xinkui Zhao, Yifan Zhang, Sai Liu +6
Multi-agent systems (MAS) have demonstrated significant effectiveness in addressing complex problems through coordinated collaboration among heterogeneous agents. However, real-wor…
A Robust Incomplete Multimodal Low-Rank Adaptation Approach for Emotion Recognition
Xinkui Zhao, Jinsong Shu, Yangyang Wu +6
Multimodal Emotion Recognition (MER) often encounters incomplete multimodality in practical applications due to sensor failures or privacy protection requirements. While existing m…
Multi-Modal One-Shot Federated Ensemble Learning for Medical Data with Vision Large Language Model
Naibo Wang, Yuchen Deng, Shichen Fan +2
Federated learning (FL) has attracted considerable interest in the medical domain due to its capacity to facilitate collaborative model training while maintaining data privacy. How…
Data-Free Federated Class Incremental Learning with Diffusion-Based Generative Memory
Naibo Wang, Yuchen Deng, Wenjie Feng +2
Federated Class Incremental Learning (FCIL) is a critical yet largely underexplored issue that deals with the dynamic incorporation of new classes within federated learning (FL). E…
One-Shot Sequential Federated Learning for Non-IID Data by Enhancing Local Model Diversity
Naibo Wang, Yuchen Deng, Wenjie Feng +3
Traditional federated learning mainly focuses on parallel settings (PFL), which can suffer significant communication and computation costs. In contrast, one-shot and sequential fed…
Data-Free Diversity-Based Ensemble Selection For One-Shot Federated Learning in Machine Learning Model Market
Naibo Wang, Wenjie Feng, Fusheng Liu +2
The emerging availability of trained machine learning models has put forward the novel concept of Machine Learning Model Market in which one can harness the collective intelligence…
A Latent Feelings-aware RNN Model for User Churn Prediction with Behavioral Data
Meng Xi, Zhiling Luo, Naibo Wang +1
Predicting user churn and taking personalized measures to retain users is a set of common and effective practices for online game operators. However, different from the traditional…
Service Wrapper: a system for converting web data into web services
Naibo Wang, Zhiling Luo, Xiya Lyu +2
Web services are widely used in many areas via callable APIs, however, data are not always available in this way. We always need to get some data from web pages whose structure is…