160 citations · 168 across the 14 of their papers we have counts for
5 papers · 1 filter
Can LLMs Help You at Work? A Sandbox for Evaluating LLM Agents in Enterprise Environments
Harsh Vishwakarma, Ankush Agarwal, Ojas Patil +2
Enterprise systems are crucial for enhancing productivity and decision-making among employees and customers. Integrating LLM based systems into enterprise systems enables intellige…
Adaptive LLM Routing under Budget Constraints
Pranoy Panda, Raghav Magazine, Chaitanya Devaguptapu +2
Large Language Models (LLMs) have revolutionized natural language processing, but their varying capabilities and costs pose challenges in practical applications. LLM routing addres…
Learning Modular Structures That Generalize Out-of-Distribution
Arjun Ashok, Chaitanya Devaguptapu, Vineeth Balasubramanian
Out-of-distribution (O.O.D.) generalization remains to be a key challenge for real-world machine learning systems. We describe a method for O.O.D. generalization that, through trai…
On Initial Pools for Deep Active Learning
Akshay L Chandra, Sai Vikas Desai, Chaitanya Devaguptapu +1
Active Learning (AL) techniques aim to minimize the training data required to train a model for a given task. Pool-based AL techniques start with a small initial labeled pool and t…
On Adversarial Robustness: A Neural Architecture Search perspective
Chaitanya Devaguptapu, Devansh Agarwal, Gaurav Mittal +2
Adversarial robustness of deep learning models has gained much traction in the last few years. Various attacks and defenses are proposed to improve the adversarial robustness of mo…