6 papers
MedPrune: Topology-Efficient Multimodal Multi-Agent Communication Evolution for Medical VQA Tasks
Jiuheng Wan, Runze Li, Chen Chen +5
While medical multimodal large language models (Med-MLLMs) advance medical visual question answering (VQA), existing clinical workflow-inspired multi-agent frameworks suffer from i…
MPrune: Hierarchical Collaborative Pruning for Efficient Multi-Modal Multi-Agent Retrieval-Augmented Generation
Taolin Zhang, Weizi shao, Zijie Zhou +5
Recent advances in multi-modal retrieval-augmented generation (mRAG), which augments multi-modal large language models (MLLMs) with external knowledge, have shown that collective i…
Mechanistic Personality Analysis of LLMs: Steering Personality via Latent Feature Interventions
David Courtis, Ting Hu
Large Language Models (LLMs) have demonstrated the ability to simulate human-like OCEAN personality traits in generated text. Previous efforts have focused on prompt engineering or…
Learning Transferable Topology Priors for Multi-Agent LLM Collaboration Across Domains
Taolin Zhang, Zijie Zhou, Jiuheng Wan +4
Large language model (LLM)-based multi-agent systems have shown strong potential for complex reasoning by coordinating specialized agents through structured communication. However,…
Scaled Prompt-Tuning for Few-Shot Natural Language Generation
Ting Hu, Christoph Meinel, Haojin Yang
The increasingly Large Language Models (LLMs) demonstrate stronger language understanding and generation capabilities, while the memory demand and computation cost of fine-tuning L…
Empirical Evaluation of Post-Training Quantization Methods for Language Tasks
Ting Hu, Christoph Meinel, Haojin Yang
Transformer-based architectures like BERT have achieved great success in a wide range of Natural Language tasks. Despite their decent performance, the models still have numerous pa…