10 citations · 15 across the 9 of their papers we have counts for
9 papers
ASAP: Reimagining the Data Lifecycle using Application Semantic-Aware Processing
Milind Srivastava, Zeying Zhu, Yajie Zhou +5
Across many domains (e.g., observability, networking, security), data processing pipelines face what we refer to as the CSP problem: achieving low Cost at large Scale, while mainta…
Inverting the Hidden: Unveiling Multimodal Privacy Leakage in Collaborative LVLM Inference
Shuaifan Jin, Zhibo Wang, Qiyuan Wang +5
Collaborative inference deploys Large Vision-Language Models (LVLMs) by partitioning computation between edge devices and the cloud. While withholding raw inputs supposedly ensures…
TabQueryBench: A Query-Centric Benchmark for Synthetic Tabular Data
Jialin Zhang, Fenghao Dong, Yajie Zhou +2
Synthetic tabular data support use cases like data sharing, model development under access restrictions, and rapid prototyping of analytical workflows. Modern generative models are…
AIChilles: Automatically Uncovering Hidden Weaknesses in AI-Evolved Systems
Yajie Zhou, Ao Li, Ashwin Silla +2
The computer systems community has recently seen growing interest in AI-driven system evolution, where AI agents iteratively rewrite systems. Frameworks such as AdaEvolve and Engra…
NetArena: Dynamic Benchmarks for AI Agents in Network Automation
Yajie Zhou, Jiajun Ruan, Eric S. Wang +4
As AI agents expand into high-stakes domains like network system operations, evaluating their real-world reliability becomes increasingly critical. However, existing benchmarks ris…
AFLoRA: Adaptive Federated Fine-Tuning of Large Language Models with Resource-Aware Low-Rank Adaption
Yajie Zhou, Xiaoyi Pang, Zhibo Wang
Federated fine-tuning has emerged as a promising approach to adapt foundation models to downstream tasks using decentralized data. However, real-world deployment remains challengin…
Unveiling the Vulnerability of Private Fine-Tuning in Split-Based Frameworks for Large Language Models: A Bidirectionally Enhanced Attack
Guanzhong Chen, Zhenghan Qin, Mingxin Yang +4
Recent advancements in pre-trained large language models (LLMs) have significantly influenced various domains. Adapting these models for specific tasks often involves fine-tuning (…
Enhancing Network Management Using Code Generated by Large Language Models
Sathiya Kumaran Mani, Yajie Zhou, Kevin Hsieh +3
Analyzing network topologies and communication graphs plays a crucial role in contemporary network management. However, the absence of a cohesive approach leads to a challenging le…
Automatic Curriculum Generation for Learning Adaptation in Networking
Zhengxu Xia, Yajie Zhou, Francis Y. Yan +1
As deep reinforcement learning (RL) showcases its strengths in networking and systems, its pitfalls also come to the public's attention--when trained to handle a wide range of netw…