2 citations · 2 across the 6 of their papers we have counts for
6 papers
SmartGen: Seamless Disaggregated LLM Inference with Selective KV Cache Transfer
Xuchuan Luo, Jiacheng Shen, Xin Wang +1
Disaggregating the prefill and decoding stages of large language model (LLM) inference into two separate sets of nodes is widely adopted in today's LLM serving systems. However, su…
CIDER: Boosting Memory-Disaggregated Key-Value Stores with Pessimistic Synchronization
Yuxuan Du, Xuchuan Luo, Xin Wang +2
Memory-disaggregated key-value (KV) stores suffer from a severe performance bottleneck due to their I/O redundancy issues. A huge amount of redundant I/Os are generated when synchr…
Guided Debugging of Auto-Translated Code Using Differential Testing
Shengnan Wu, Xinyu Sun, Xin Wang +1
Large Language Models (LLMs) hold great promise in the task of code translation. However, the lack of explainability complicates the identification of the inevitable translation er…
Combating Missed Recalls in E-commerce Search: A CoT-Prompting Testing Approach
Shengnan Wu, Yongxiang Hu, Yingchuan Wang +6
Search components in e-commerce apps, often complex AI-based systems, are prone to bugs that can lead to missed recalls - situations where items that should be listed in search res…
Muffin: Testing Deep Learning Libraries via Neural Architecture Fuzzing
Jiazhen Gu, Xuchuan Luo, Yangfan Zhou +1
Deep learning (DL) techniques are proven effective in many challenging tasks, and become widely-adopted in practice. However, previous work has shown that DL libraries, the basis o…
Detecting Deep Neural Network Defects with Data Flow Analysis
Jiazhen Gu, Huanlin Xu, Yangfan Zhou +3
Deep neural networks (DNNs) are shown to be promising solutions in many challenging artificial intelligence tasks. However, it is very hard to figure out whether the low precision…