1 citations · 3 across the 25 of their papers we have counts for
10 papers · 1 filter
RCR-Router: Efficient Role-Aware Context Routing for Multi-Agent LLM Systems with Structured Memory
Jun Liu, Zhenglun Kong, Changdi Yang +12
Large language model (LLM) agents are increasingly organized into multi-agent systems for complex reasoning and decision-making tasks. However, scaling such systems can substantial…
Enabling Flexible Multi-LLM Integration for Scalable Knowledge Aggregation
Zhenglun Kong, Zheng Zhan, Shiyue Hou +10
Large language models (LLMs) have shown remarkable promise but remain challenging to continually improve through traditional finetuning, particularly when integrating capabilities…
Taming Diffusion for Dataset Distillation with High Representativeness
Lin Zhao, Yushu Wu, Xinru Jiang +5
Recent deep learning models demand larger datasets, driving the need for dataset distillation to create compact, cost-efficient datasets while maintaining performance. Due to the p…
FastCar: Cache Attentive Replay for Fast Auto-Regressive Video Generation on the Edge
Xuan Shen, Weize Ma, Yufa Zhou +11
Auto-regressive (AR) models, initially successful in language generation, have recently shown promise in visual generation tasks due to their superior sampling efficiency. Unlike i…
DraftAttention: Fast Video Diffusion via Low-Resolution Attention Guidance
Xuan Shen, Chenxia Han, Yufa Zhou +7
Diffusion transformer-based video generation models (DiTs) have recently attracted widespread attention for their excellent generation quality. However, their computational cost re…
Structured Agent Distillation for Large Language Model
Jun Liu, Zhenglun Kong, Peiyan Dong +10
Large language models (LLMs) exhibit strong capabilities as decision-making agents by interleaving reasoning and actions, as seen in ReAct-style frameworks. Yet, their practical de…
QuartDepth: Post-Training Quantization for Real-Time Depth Estimation on the Edge
Xuan Shen, Weize Ma, Jing Liu +9
Monocular Depth Estimation (MDE) has emerged as a pivotal task in computer vision, supporting numerous real-world applications. However, deploying accurate depth estimation models…
RoRA: Efficient Fine-Tuning of LLM with Reliability Optimization for Rank Adaptation
Jun Liu, Zhenglun Kong, Peiyan Dong +10
Fine-tuning helps large language models (LLM) recover degraded information and enhance task performance. Although Low-Rank Adaptation (LoRA) is widely used and effective for fine-t…
Open-Source Acceleration of Stable-Diffusion.cpp Deployable on All Devices
Jingxu Ng, Cheng Lv, Pu Zhao +5
Stable diffusion plays a crucial role in generating high-quality images. However, image generation is time-consuming and memory-intensive. To address this, stable-diffusion.cpp (Sd…
Efficient Reasoning with Hidden Thinking
Xuan Shen, Yizhou Wang, Yufa Zhou +4
Chain-of-Thought (CoT) reasoning has become a powerful framework for improving complex problem-solving capabilities in Multimodal Large Language Models (MLLMs). However, the verbos…