5 citations · 9 across the 22 of their papers we have counts for
9 papers · 1 filter
To Keep or Not to Keep: Learning KV Cache Retention in Disaggregated LLM Serving Systems
Dong Liu, Yanxuan Yu, Eric Jiang +2
Disaggregated \textsc{LLM} serving separates prefill and decode across node pools, placing a network fabric between \textsc{KV}-cache computation and consumption. This breaks a key…
RUBRIC: Realism--Utility Balanced Ranking for Imbalanced Classification
Yanxuan Yu, Dong Liu, Shu Wang +9
Class imbalance poses a fundamental challenge in risk-sensitive applications such as fraud detection and medical diagnosis, where minority-class samples are scarce yet critical for…
Accelerating Frequency Domain Diffusion Models with Error-Feedback Event-Driven Caching
Dong Liu, Yanxuan Yu, Ying Nian Wu
Diffusion models achieve remarkable success in time series generation. However, slow inference limits their practical deployment. We propose E-CRF (Error-Feedback Event-Driven…
MKA: Memory-Keyed Attention for Efficient Long-Context Reasoning
Dong Liu, Yanxuan Yu, Ben Lengerich +1
As long-context language modeling becomes increasingly important, the cost of maintaining and attending to large Key/Value (KV) caches grows rapidly, becoming a major bottleneck in…
Boundary-Aware Adversarial Filtering for Reliable Diagnosis under Extreme Class Imbalance
Yanxuan Yu, Michael S. Hughes, Julien Lee +2
We study classification under extreme class imbalance where recall and calibration are both critical, for example in medical diagnosis scenarios. We propose AF-SMOTE, a mathematica…
FastCache: Fast Caching for Diffusion Transformer Through Learnable Linear Approximation
Dong Liu, Yanxuan Yu, Jiayi Zhang +3
Diffusion Transformers (DiT) are powerful generative models but remain computationally intensive due to their iterative structure and deep transformer stacks. To alleviate this ine…
MobileNetV2: A lightweight classification model for home-based sleep apnea screening
Hui Pan, Yanxuan Yu, Jilun Ye +1
This study proposes a novel lightweight neural network model leveraging features extracted from electrocardiogram (ECG) and respiratory signals for early OSA screening. ECG signals…
LLMEasyQuant: Scalable Quantization for Parallel and Distributed LLM Inference
Dong Liu, Yanxuan Yu
As large language models (LLMs) grow in size and deployment scale, quantization has become an essential technique for reducing memory footprint and improving inference efficiency.…
Efficient Graph Optimization via Distance-Aware Graph Representation Learning
Dong Liu, Yanxuan Yu
We propose an efficient framework that integrates distance-aware multi-hop message passing with dynamic topology refinement. Unlike standard GNNs that rely on shallow, fixed-hop ag…