11 citations · 43 across the 12 of their papers we have counts for
12 papers
Granite-Function Calling Model: Introducing Function Calling Abilities via Multi-task Learning of Granular Tasks
Ibrahim Abdelaziz, Kinjal Basu, Mayank Agarwal +23
Large language models (LLMs) have recently shown tremendous promise in serving as the backbone to agentic systems, as demonstrated by their performance in multi-faceted, challengin…
TESS: A Multi-intent Parser for Conversational Multi-Agent Systems with Decentralized Natural Language Understanding Models
Burak Aksar, Yara Rizk, Tathagata Chakraborti
Chatbots have become one of the main pathways for the delivery of business automation tools. Multi-agent systems offer a framework for designing chatbots at scale, making it easier…
TaskDiff: A Similarity Metric for Task-Oriented Conversations
Ankita Bhaumik, Praveen Venkateswaran, Yara Rizk +1
The popularity of conversational digital assistants has resulted in the availability of large amounts of conversational data which can be utilized for improved user experience and…
A Case for Business Process-Specific Foundation Models
Yara Rizk, Praveen Venkateswaran, Vatche Isahagian +1
The inception of large language models has helped advance state-of-the-art performance on numerous natural language tasks. This has also opened the door for the development of foun…
Natural Language Sentence Generation from API Specifications
Siyu Huo, Kushal Mukherjee, Jayachandu Bandlamudi +3
APIs are everywhere; they provide access to automation solutions that could help businesses automate some of their tasks. Unfortunately, they may not be accessible to the business…
Extending LIME for Business Process Automation
Sohini Upadhyay, Vatche Isahagian, Vinod Muthusamy +1
AI business process applications automate high-stakes business decisions where there is an increasing demand to justify or explain the rationale behind algorithmic decisions. Busin…
Explainable Composition of Aggregated Assistants
Sarath Sreedharan, Tathagata Chakraborti, Yara Rizk +1
A new design of an AI assistant that has become increasingly popular is that of an "aggregated assistant" -- realized as an orchestrated composition of several individual skills or…
From Robotic Process Automation to Intelligent Process Automation: Emerging Trends
Tathagata Chakraborti, Vatche Isahagian, Rania Khalaf +4
In this survey, we study how recent advances in machine intelligence are disrupting the world of business processes. Over the last decade, there has been steady progress towards th…
A Conversational Digital Assistant for Intelligent Process Automation
Yara Rizk, Vatche Isahagian, Scott Boag +4
Robotic process automation (RPA) has emerged as the leading approach to automate tasks in business processes. Moving away from back-end automation, RPA automated the mouse-click on…
A Snooze-less User-Aware Notification System for Proactive Conversational Agents
Yara Rizk, Vatche Isahagian, Merve Unuvar +1
The ubiquity of smart phones and electronic devices has placed a wealth of information at the fingertips of consumers as well as creators of digital content. This has led to millio…
A Unified Conversational Assistant Framework for Business Process Automation
Yara Rizk, Abhishek Bhandwalder, Scott Boag +5
Business process automation is a booming multi-billion-dollar industry that promises to remove menial tasks from workers' plates -- through the introduction of autonomous agents --…
An Optimized and Energy-Efficient Parallel Implementation of Non-Iteratively Trained Recurrent Neural Networks
Julia El Zini, Yara Rizk, Mariette Awad
Recurrent neural networks (RNN) have been successfully applied to various sequential decision-making tasks, natural language processing applications, and time-series predictions. S…