32 citations · 34 across the 12 of their papers we have counts for
12 papers
KVReviver: Reversible KV Cache Compression with Sketch-Based Token Reconstruction
Aomufei Yuan, Zhiming Wang, Ruijie Miao +8
As the context length of current large language models (LLMs) rapidly increases, the memory demand for the Key-Value (KV) cache is becoming a bottleneck for LLM deployment and batc…
MagnifierSketch: Quantile Estimation Centered at One Point
Jiarui Guo, Qiushi Lyu, Yuhan Wu +6
In this paper, we take into consideration quantile estimation in data stream models, where every item in the data stream is a key-value pair. Researchers sometimes aim to estimate…
ScholarSearch: Benchmarking Scholar Searching Ability of LLMs
Junting Zhou, Wang Li, Yiyan Liao +5
Large Language Models (LLMs)' search capabilities have garnered significant attention. Existing benchmarks, such as OpenAI's BrowseComp, primarily focus on general search scenarios…
Detecting Flow Gaps in Data Streams
Siyuan Dong, Yuxuan Tian, Wenhan Ma +5
Data stream monitoring is a crucial task which has a wide range of applications. The majority of existing research in this area can be broadly classified into two types, monitoring…
ResidualSketch: Enhancing Layer Efficiency and Error Reduction in Hierarchical Heavy Hitter Detection with ResNet Innovations
Xilai Liu, Yuxuan Tian, Xiangyuan Wang +4
In network management, swiftly and accurately identifying traffic anomalies, including Distributed Denial-of-Service (DDoS) attacks and unexpected network disruptions, is essential…
Hidden Sketch: A Space-Efficient Reversible Sketch for Tracking Frequent Items in Data Streams
Zicang Xu, Yuxuan Tian, Yuhan Wu +1
Modern data stream applications demand memory-efficient solutions for accurately tracking frequent items, such as heavy hitters and heavy changers, under strict resource constraint…
Carbonyl4: A Sketch for Set-Increment Mixed Updates
Yikai Zhao, Yuhan Wu, Tong Yang
In the realm of data stream processing, the advent of SET-INCREMENT Mixed (SIM) data streams necessitates algorithms that efficiently handle both SET and INCREMENT operations. We p…
INT-FlashAttention: Enabling Flash Attention for INT8 Quantization
Shimao Chen, Zirui Liu, Zhiying Wu +6
As the foundation of large language models (LLMs), self-attention module faces the challenge of quadratic time and memory complexity with respect to sequence length. FlashAttention…
Approaching 100% Confidence in Stream Summary through ReliableSketch
Yuhan Wu, Hanbo Wu, Xilai Liu +6
To approximate sums of values in key-value data streams, sketches are widely used in databases and networking systems. They offer high-confidence approximations for any given key w…
SimiSketch: Efficiently Estimating Similarity of streaming Multisets
Fenghao Dong, Yang He, Yutong Liang +4
The challenge of estimating similarity between sets has been a significant concern in data science, finding diverse applications across various domains. However, previous approache…
ChainedFilter: Combining Membership Filters by Chain Rule
Haoyu Li, Liuhui Wang, Qizhi Chen +5
Membership (membership query / membership testing) is a fundamental problem across databases, networks and security. However, previous research has primarily focused on either appr…
ChameleMon: Shifting Measurement Attention as Network State Changes
Kaicheng Yang, Yuhan Wu, Ruijie Miao +8
Flow-level network measurement is critical to many network applications. Among various measurement tasks, packet loss detection and heavy-hitter detection are two most important me…