3 citations · 4 across the 9 of their papers we have counts for
9 papers
FixItFlow: Automated Troubleshooting Guide Generation from Cloud Incidents
Srihari Unnikrishnan, Jaskaran Singh Walia, Drishti Goel +1
Cloud services experience frequent incidents that require rapid diagnosis and resolution. Troubleshooting guides help engineers respond consistently, but creating them manually is…
PETRA: Transforming Web Text for Petroleum-Engineering Domain Adaptation
Kirill Dubovikov, Omar El Mansouri, Hachem Madmoun +12
Petroleum-engineering search exposes a supervision gap for strong general retrievers: relevant evidence exists in public web text, but domain relevance labels are scarce. To addres…
eARCO: Efficient Automated Root Cause Analysis with Prompt Optimization
Drishti Goel, Raghav Magazine, Supriyo Ghosh +5
Root cause analysis (RCA) for incidents in large-scale cloud systems is a complex, knowledge-intensive task that often requires significant manual effort from on-call engineers (OC…
Streetwise Agents: Empowering Offline RL Policies to Outsmart Exogenous Stochastic Disturbances in RTC
Aditya Soni, Mayukh Das, Anjaly Parayil +8
The difficulty of exploring and training online on real production systems limits the scope of real-time online data/feedback-driven decision making. The most feasible approach is…
CARMO: Dynamic Criteria Generation for Context-Aware Reward Modelling
Taneesh Gupta, Shivam Shandilya, Xuchao Zhang +5
Reward modeling in large language models is susceptible to reward hacking, causing models to latch onto superficial features such as the tendency to generate lists or unnecessarily…
TACO-RL: Task Aware Prompt Compression Optimization with Reinforcement Learning
Shivam Shandilya, Menglin Xia, Supriyo Ghosh +4
The increasing prevalence of large language models (LLMs) such as GPT-4 in various applications has led to a surge in the size of prompts required for optimal performance, leading…
X-lifecycle Learning for Cloud Incident Management using LLMs
Drishti Goel, Fiza Husain, Aditya Singh +5
Incident management for large cloud services is a complex and tedious process and requires significant amount of manual efforts from on-call engineers (OCEs). OCEs typically levera…
Dependency Aware Incident Linking in Large Cloud Systems
Supriyo Ghosh, Karish Grover, Jimmy Wong +4
Despite significant reliability efforts, large-scale cloud services inevitably experience production incidents that can significantly impact service availability and customer's sat…
Automated Root Causing of Cloud Incidents using In-Context Learning with GPT-4
Xuchao Zhang, Supriyo Ghosh, Chetan Bansal +4
Root Cause Analysis (RCA) plays a pivotal role in the incident diagnosis process for cloud services, requiring on-call engineers to identify the primary issues and implement correc…