5 citations · 9 across the 22 of their papers we have counts for
26 papers
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…
MeshKV: A Network-on-Chip KV Cache Fabric for Scalable Transformer Decoding Accelerators
Dong Liu, Yanxuan Yu
Autoregressive transformer decoding is constrained by irregular key-value (KV) cache movement on tiled accelerators. Prior compression and DRAM-placement systems still concentrate…
Privacy-Preserving Topology-Guided Safety for LLM-Based Multi-Agent Systems via Federated Graph Learning
Jinxi Yu, Eric Hanchen Jiang, Levina Li +6
Topology-guided safeguards for LLM-based multi-agent systems (MAS) train a GNN over the inter-agent communication graph to localize risky agents and intervene on the topology---but…
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…
HSMLA: Hierarchical Softmax Multi-scale Linear Attention for Efficient Vision Transformers
Dong Liu, Yanxuan Yu, Renata Borovica-Gajic +2
Vision transformers face significant computational overheads in high-resolution dense prediction due to the quadratic complexity of self-attention. Linear attention offers efficien…
OLIVE: Online Low-Rank Incremental Learning for Efficient Adaptive Exoskeletons
Dong Liu, Yanxuan Yu, Ben Lengerich +2
Wearable exoskeleton systems hold promise for restoring mobility in individuals with physical impairments, yet most existing controllers rely on static gait policies that cannot ad…
Thoughts-as-Planning: Latent World Models for Chain-of-Thoughts Optimization via Reinforcement Planning
Dong Liu, Yanxuan Yu, Ying Nian Wu
The success of large language models (LLMs) across diverse NLP tasks has elevated the importance of reasoning chain optimization as a critical step in aligning model behavior with…
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…
AdaCorrection: Adaptive Offset Cache Correction for Accurate Diffusion Transformers
Dong Liu, Yanxuan Yu, Ben Lengerich +1
Diffusion Transformers (DiTs) achieve state-of-the-art performance in high-fidelity image and video generation but suffer from expensive inference due to their iterative denoising…
CXL-SpecKV: A Disaggregated FPGA Speculative KV-Cache for Datacenter LLM Serving
Dong Liu, Yanxuan Yu
Large Language Models (LLMs) have revolutionized natural language processing tasks, but their deployment in datacenter environments faces significant challenges due to the massive…
CSV-Decode: Certifiable Sub-Vocabulary Decoding for Efficient Large Language Model Inference
Dong Liu, Shu Wang, Yanxuan Yu +2
Large language models face significant computational bottlenecks during inference due to the expensive output layer computation over large vocabularies. We present CSV-Decode, a no…
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…
SPI: Query-Depth-Adaptive Indexing for Streaming RAG in Vector Databases
Dong Liu, Yanxuan Yu
Vector databases (VecDBs) are increasingly deployed in retrieval-augmented generation (RAG) pipelines where query processing and document ingestion occur concurrently. The index la…
-Attention: Online Efficient Sparse Transformers for Long-Context Modeling
Pike D. Liu, Chang Liu, Yanxuan Yu
Sparse attention is crucial in long-context Transformers, which restricts each token to a limited neighborhood and thereby reduces the quadratic cost of full self-attention. Local…
Cognitive Load Traces as Symbolic and Visual Accounts of Deep Model Cognition
Dong Liu, Yanxuan Yu
We propose \textbf{Cognitive Load Traces} (CLTs) as a mid-level interpretability framework for deep models, inspired by Cognitive Load Theory in human cognition. CLTs are defined a…
HSGM: Hierarchical Segment-Graph Memory for Scalable Long-Text Semantics
Dong Liu, Yanxuan Yu
Semantic parsing of long documents remains challenging due to quadratic growth in pairwise composition and memory requirements. We introduce \textbf{Hierarchical Segment-Graph Memo…
TinyServe: Query-Aware Cache Selection for Efficient LLM Serving
Dong Liu, Yanxuan Yu
Serving large language models (LLMs) efficiently remains challenging due to the high memory and latency overhead of key-value (KV) cache access during autoregressive decoding. We p…
SemToken: Semantic-Aware Tokenization for Efficient Long-Context Language Modeling
Dong Liu, Yanxuan Yu
Tokenization plays a critical role in language modeling, yet existing approaches such as Byte-Pair Encoding (BPE) or WordPiece operate purely on frequency statistics, ignoring the…
QuickMerge++: Fast Token Merging with Autoregressive Prior
Dong Liu, Yanxuan Yu
As generative models scale to larger inputs across language, vision, and video domains, the cost of token-level computation has become a key bottleneck. While prior work suggests t…
PiKV: KV Cache Management System for Mixture of Experts
Dong Liu, Yanxuan Yu, Ben Lengerich +1
As large-scale language models continue to scale up in both size and context length, the memory and communication cost of key-value (KV) cache storage has become a major bottleneck…
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…
Designing Large Foundation Models for Efficient Training and Inference: A Survey
Dong Liu, Yanxuan Yu, Yite Wang +5
This paper focuses on modern efficient training and inference technologies on foundation models and illustrates them from two perspectives: model and system design. Model and Syste…