6 citations · 18 across the 16 of their papers we have counts for
16 papers
AdNanny: One Reasoning LLM for All Offline Ads Recommendation Tasks
Nan Hu, Han Li, Jimeng Sun +16
Large Language Models (LLMs) have shown strong capabilities in Natural Language Understanding and Generation, but deploying them directly in online advertising systems is often imp…
Large Action Models: From Inception to Implementation
Lu Wang, Fangkai Yang, Chaoyun Zhang +15
As AI continues to advance, there is a growing demand for systems that go beyond language-based assistance and move toward intelligent agents capable of performing real-world actio…
An Advanced Reinforcement Learning Framework for Online Scheduling of Deferrable Workloads in Cloud Computing
Hang Dong, Liwen Zhu, Zhao Shan +10
Efficient resource utilization and perfect user experience usually conflict with each other in cloud computing platforms. Great efforts have been invested in increasing resource ut…
Verco: Learning Coordinated Verbal Communication for Multi-agent Reinforcement Learning
Dapeng Li, Hang Dong, Lu Wang +8
In recent years, multi-agent reinforcement learning algorithms have made significant advancements in diverse gaming environments, leading to increased interest in the broader appli…
UFO: A UI-Focused Agent for Windows OS Interaction
Chaoyun Zhang, Liqun Li, Shilin He +9
We introduce UFO, an innovative UI-Focused agent to fulfill user requests tailored to applications on Windows OS, harnessing the capabilities of GPT-Vision. UFO employs a dual-agen…
Contrastive Learning with Negative Sampling Correction
Lu Wang, Chao Du, Pu Zhao +8
As one of the most effective self-supervised representation learning methods, contrastive learning (CL) relies on multiple negative pairs to contrast against each positive pair. In…
COIN: Chance-Constrained Imitation Learning for Uncertainty-aware Adaptive Resource Oversubscription Policy
Lu Wang, Mayukh Das, Fangkai Yang +9
We address the challenge of learning safe and robust decision policies in presence of uncertainty in context of the real scientific problem of adaptive resource oversubscription to…
Risk-aware Adaptive Virtual CPU Oversubscription in Microsoft Cloud via Prototypical Human-in-the-loop Imitation Learning
Lu Wang, Mayukh Das, Fangkai Yang +11
Oversubscription is a prevalent practice in cloud services where the system offers more virtual resources, such as virtual cores in virtual machines, to users or applications than…
Counter-Empirical Attacking based on Adversarial Reinforcement Learning for Time-Relevant Scoring System
Xiangguo Sun, Hong Cheng, Hang Dong +3
Scoring systems are commonly seen for platforms in the era of big data. From credit scoring systems in financial services to membership scores in E-commerce shopping platforms, pla…
TaskWeaver: A Code-First Agent Framework
Bo Qiao, Liqun Li, Xu Zhang +16
Large Language Models (LLMs) have shown impressive abilities in natural language understanding and generation, leading to their widespread use in applications such as chatbots and…
Diffusion-based Time Series Data Imputation for Microsoft 365
Fangkai Yang, Wenjie Yin, Lu Wang +10
Reliability is extremely important for large-scale cloud systems like Microsoft 365. Cloud failures such as disk failure, node failure, etc. threaten service reliability, resulting…
Robust Positive-Unlabeled Learning via Noise Negative Sample Self-correction
Zhangchi Zhu, Lu Wang, Pu Zhao +7
Learning from positive and unlabeled data is known as positive-unlabeled (PU) learning in literature and has attracted much attention in recent years. One common approach in PU lea…
Assess and Summarize: Improve Outage Understanding with Large Language Models
Pengxiang Jin, Shenglin Zhang, Minghua Ma +13
Cloud systems have become increasingly popular in recent years due to their flexibility and scalability. Each time cloud computing applications and services hosted on the cloud are…
Learning Cooperative Oversubscription for Cloud by Chance-Constrained Multi-Agent Reinforcement Learning
Junjie Sheng, Lu Wang, Fangkai Yang +9
Oversubscription is a common practice for improving cloud resource utilization. It allows the cloud service provider to sell more resources than the physical limit, assuming not al…
Fast Outage Analysis of Large-scale Production Clouds with Service Correlation Mining
Yaohui Wang, Guozheng Li, Zijian Wang +13
Cloud-based services are surging into popularity in recent years. However, outages, i.e., severe incidents that always impact multiple services, can dramatically affect user experi…
CloudDet: Interactive Visual Analysis of Anomalous Performances in Cloud Computing Systems
Ke Xu, Yun Wang, Leni Yang +6
Detecting and analyzing potential anomalous performances in cloud computing systems is essential for avoiding losses to customers and ensuring the efficient operation of the system…