1 citations · 1 across the 12 of their papers we have counts for
13 papers
EchoCache: Energy-Guided Cross-Modal Caching for Efficient Audio-Driven Video Generation
Jiayu Chen, Xiaoyu Wu, Rongshan Gao +6
Audio-driven video generation (A2V) has achieved promising progress in synthesizing temporally coherent and audio-visually aligned videos, yet its inference remains expensive due t…
Token Radius Attention for Efficient Video Generation
Jiayu Chen, Zhikun Jiang, Maoliang Li +6
Video Diffusion Transformers (VDiTs) enable high-fidelity generation but incur quadratic cost from dense 3D self-attention. Existing head- and block-level sparse methods share comp…
EcoVideo: Entropy-Orchestrated Video Generation Paradigm in Cloud-Edge Dynamics
Jiayu Chen, Hengyi Zhang, Maoliang Li +5
DiT video generation is latency-intensive due to iterative full-frame denoising, while prior cloud-edge methods largely rely on static inter-step decoupling and cannot leverage int…
SAC: Disaggregated KV Cache System for Sparse Attention LLMs with CXL
Ruiyang Ma, Teng Ma, Junru Li +7
The scaling of LLMs toward long-context inference has shifted the primary serving system bottleneck from computation to memory capacity. Traditional solutions for dense attention m…
Pyramid Forcing: Head-Aware Pyramid KV Cache Policy for High-Quality Long Video Generation
Jiayu Chen, Junbei Tang, Wenbiao Zhao +6
Autoregressive video generation enables streaming and open-ended long video synthesis, but still suffers from long-term degradation caused by accumulated errors. Existing KVCache s…
RoboECC: Multi-Factor-Aware Edge-Cloud Collaborative Deployment for VLA Models
Zihao Zheng, Hangyu Cao, Jiayu Chen +6
Vision-Language-Action (VLA) models are mainstream in embodied intelligence but face high inference costs. Edge-Cloud Collaborative (ECC) deployment offers an effective fix by easi…
2D or 3D: Who Governs Salience in VLA Models? -- Tri-Stage Token Pruning Framework with Modality Salience Awareness
Zihao Zheng, Sicheng Tian, Zhihao Mao +8
Vision-Language-Action (VLA) models have emerged as the mainstream of embodied intelligence. Recent VLA models have expanded their input modalities from 2D-only to 2D+3D paradigms,…
ActECC: Action Chunk Temporal Harnessing for Edge-Cloud Collaborative VLA Inference System
Zihao Zheng, Sicheng Tian, Zhihao Mao +10
VLA models have emerged as the mainstream for embodied intelligence, which decouples reasoning and execution via action chunks. To enable real-time deployment of VLA models, existi…
Pooling Engram Conditional Memory in Large Language Models using CXL
Ruiyang Ma, Teng Ma, Zhiyuan Su +11
Engram conditional memory has emerged as a promising component for LLMs by decoupling static knowledge lookup from dynamic computation. Since Engram exhibits sparse access patterns…
ToProVAR: Efficient Visual Autoregressive Modeling via Tri-Dimensional Entropy-Aware Semantic Analysis and Sparsity Optimization
Jiayu Chen, Ruoyu Lin, Zihao Zheng +4
Visual Autoregressive(VAR) models enhance generation quality but face a critical efficiency bottleneck in later stages. In this paper, we present a novel optimization framework for…
UltraSketchLLM: Sub-1-Bit LLM Compression via Sketch and Hardware-Friendly Operators
Sunan Zou, Xueting Sun, Ziyun Zhang +1
Large language models (LLMs) require larger GPU memory size these days, necessitating efficient and extreme weight compression methods. Existing compression methods are either theo…
Pseudo-Knowledge Graph: Meta-Path Guided Retrieval and In-Graph Text for RAG-Equipped LLM
Yuxin Yang, Haoyang Wu, Tao Wang +3
The advent of Large Language Models (LLMs) has revolutionized natural language processing. However, these models face challenges in retrieving precise information from vast dataset…
WideSA: A High Array Utilization Mapping Scheme for Uniform Recurrences on the Versal ACAP Architecture
Tuo Dai, Bizhao Shi, Guojie Luo
The Versal Adaptive Compute Acceleration Platform (ACAP) is a new architecture that combines AI Engines (AIEs) with reconfigurable fabric. This architecture offers significant acce…