4 papers
Context Learning for Multi-Agent Discussion
Xingyuan Hua, Sheng Yue, Xinyi Li +3
Multi-Agent Discussion (MAD) has garnered increasing attention very recently, where multiple LLM instances collaboratively solve problems via structured discussion. However, we fin…
DynaKV: Enabling Accurate and Efficient Long-Sequence LLM Decoding on Smartphones
Tuowei Wang, Minxing Huang, Fengzu Li +3
As the demand for human-like reasoning, multi-turn dialogues, and long-form responses grows, large language models (LLMs) are increasingly expected to support efficient and effecti…
LLM-Driven Self-Refinement for Embodied Drone Task Planning
Deyu Zhang, Xicheng Zhang, Jiahao Li +6
We introduce SRDrone, a novel system designed for self-refinement task planning in industrial-grade embodied drones. SRDrone incorporates two key technical contributions: First, it…
Prompt-aware of Frame Sampling for Efficient Text-Video Retrieval
Deyu Zhang, Tingting Long, Jinrui Zhang +3
Enabling efficient text-video retrieval on edge-end devices is critical for real-world applications. Yet, existing methods face a critical challenge in balancing accuracy and compu…