research
∙
08/18/2023
WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct
Large language models (LLMs), such as GPT-4, have shown remarkable perfo...
share
research
∙
08/03/2023
Diffusion-based Time Series Data Imputation for Microsoft 365
Reliability is extremely important for large-scale cloud systems like Mi...
research
∙
08/01/2023
Robust Positive-Unlabeled Learning via Noise Negative Sample Self-correction
Learning from positive and unlabeled data is known as positive-unlabeled...
research
∙
07/03/2023
ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly Detection
Anomaly detection in multivariate time series data is of paramount impor...
research
∙
06/14/2023
WizardCoder: Empowering Code Large Language Models with Evol-Instruct
Code Large Language Models (Code LLMs), such as StarCoder, have demonstr...
research
∙
05/29/2023
Assess and Summarize: Improve Outage Understanding with Large Language Models
Cloud systems have become increasingly popular in recent years due to th...
research
∙
05/25/2023
Empowering Practical Root Cause Analysis by Large Language Models for Cloud Incidents
Ensuring the reliability and availability of cloud services necessitates...
research
∙
05/19/2023
Introspective Tips: Large Language Model for In-Context Decision Making
The emergence of large language models (LLMs) has substantially influenc...
research
∙
05/19/2023
Empower Large Language Model to Perform Better on Industrial Domain-Specific Question Answering
Large Language Model (LLM) has gained popularity and achieved remarkable...
research
∙
05/08/2023
Augmented Large Language Models with Parametric Knowledge Guiding
Large Language Models (LLMs) have significantly advanced natural languag...
research
∙
04/22/2023
Did We Miss Something Important? Studying and Exploring Variable-Aware Log Abstraction
Due to the sheer size of software logs, developers rely on automated tec...
research
∙
02/19/2023
Incident-aware Duplicate Ticket Aggregation for Cloud Systems
In cloud systems, incidents are potential threats to customer satisfacti...
research
∙
02/14/2023
Conservative State Value Estimation for Offline Reinforcement Learning
Offline reinforcement learning faces a significant challenge of value ov...
research
∙
11/21/2022
Learning Cooperative Oversubscription for Cloud by Chance-Constrained Multi-Agent Reinforcement Learning
Oversubscription is a common practice for improving cloud resource utili...
research
∙
11/10/2022
MMDialog: A Large-scale Multi-turn Dialogue Dataset Towards Multi-modal Open-domain Conversation
Responding with multi-modal content has been recognized as an essential ...
research
∙
09/17/2022
Enhanced Fairness Testing via Generating Effective Initial Individual Discriminatory Instances
Fairness testing aims at mitigating unintended discrimination in the dec...
research
∙
07/20/2022
Solving the Batch Stochastic Bin Packing Problem in Cloud: A Chance-constrained Optimization Approach
This paper investigates a critical resource allocation problem in the fi...
research
∙
04/09/2022
Distributed Evolution Strategies for Black-box Stochastic Optimization
This work concerns the evolutionary approaches to distributed stochastic...
research
∙
02/14/2022
UniParser: A Unified Log Parser for Heterogeneous Log Data
Logs provide first-hand information for engineers to diagnose failures i...
research
∙
11/22/2021
A Surrogate Objective Framework for Prediction+Optimization with Soft Constraints
Prediction+optimization is a common real-world paradigm where we have to...
research
∙
02/27/2020
Improving the Performance of Stochastic Local Search for Maximum Vertex Weight Clique Problem Using Programming by Optimization
The maximum vertex weight clique problem (MVWCP) is an important general...
research
∙
05/20/2019