17 citations · 19 across the 9 of their papers we have counts for
9 papers
Capacity Planning and Scheduling for Jobs with Uncertainty in Resource Usage and Duration
Sunandita Patra, Mehtab Pathan, Mahmoud Mahfouz +4
Organizations around the world schedule jobs (programs) regularly to perform various tasks dictated by their end users. With the major movement towards using a cloud computing infr…
Acting and Planning with Hierarchical Operational Models on a Mobile Robot: A Study with RAE+UPOM
Oscar Lima, Marc Vinci, Sunandita Patra +6
Robotic task execution faces challenges due to the inconsistency between symbolic planner models and the rich control structures actually running on the robot. In this paper, we pr…
GenPlanX. Generation of Plans and Execution
Daniel Borrajo, Giuseppe Canonaco, Tomás de la Rosa +10
Classical AI Planning techniques generate sequences of actions for complex tasks. However, they lack the ability to understand planning tasks when provided using natural language.…
QBD-RankedDataGen: Generating Custom Ranked Datasets for Improving Query-By-Document Search Using LLM-Reranking with Reduced Human Effort
Sriram Gopalakrishnan, Sunandita Patra
The Query-By-Document (QBD) problem is an information retrieval problem where the query is a document, and the retrieved candidates are documents that match the query document, oft…
Creating a Causally Grounded Rating Method for Assessing the Robustness of AI Models for Time-Series Forecasting
Kausik Lakkaraju, Rachneet Kaur, Parisa Zehtabi +5
AI models, including both time-series-specific and general-purpose Foundation Models (FMs), have demonstrated strong potential in time-series forecasting across sectors like financ…
Rating Multi-Modal Time-Series Forecasting Models (MM-TSFM) for Robustness Through a Causal Lens
Kausik Lakkaraju, Rachneet Kaur, Zhen Zeng +4
AI systems are notorious for their fragility; minor input changes can potentially cause major output swings. When such systems are deployed in critical areas like finance, the cons…