Integrating Efficient Model-Learning and Problem-Solving Algorithms in Permutation Environments. - Prasad Chalasani; Oren Etzioni; John Mount (KR, 1991)

Learning Switching Concepts. - Avrim Blum; Prasad Chalasani (COLT, 1992)

On Learning Embedded Symmetric Concepts. - Avrim Blum; Prasad Chalasani; Jeffrey C. Jackson (COLT, 1993)

An On-Line Algorithm for Improving Performance in Navigation - Avrim Blum; Prasad Chalasani (FOCS, 1993)

The minimum latency problem. - Avrim Blum; Prasad Chalasani; Don Coppersmith; William R. Pulleyblank; Prabhakar Raghavan; Madhu Sudan 001 (STOC, 1994)

A constant-factor approximation for the k-MST problem in the plane. - Avrim Blum; Prasad Chalasani; Santosh S. Vempala (STOC, 1995)

Query Restart Strategies for Web Agent. - Prasad Chalasani; Somesh Jha; Onn Shehory; Katia P. Sycara (Agents, 1998)

A Formal Treatment of Distributed Matchmaking. - Somesh Jha; Prasad Chalasani; Onn Shehory; Katia P. Sycara (Agents, 1998)

Increasing Resource Utilization and Task Performance by Agent Cloning. - Onn Shehory; Katia P. Sycara; Prasad Chalasani; Somesh Jha (ATAL, 1998)

Strategies for Querying Information Agents. - Prasad Chalasani; Somesh Jha; Onn Shehory; Katia P. Sycara (CIA, 1998)

Agent Cloning. - Onn Shehory; Katia P. Sycara; Prasad Chalasani; Somesh Jha (ICMAS, 1998)

Agent cloning: an approach to agent mobility and resource allocation. - Onn Shehory; Katia P. Sycara; Prasad Chalasani; Somesh Jha (IEEE Commun. Mag., 1998)

Learning with Unreliable Boundary Queries. - Avrim Blum; Prasad Chalasani; Sally A. Goldman; Donna K. Slonim (J. Comput. Syst. Sci., 1998)

A Constant-Factor Approximation Algorithm for the Geometric k-MST Problem in the Plane. - Joseph S. B. Mitchell; Avrim Blum; Prasad Chalasani; Santosh S. Vempala (SIAM J. Comput., 1998)

Approximate Option Pricing. - Prasad Chalasani; Somesh Jha; Isaac Saias (Algorithmica, 1999)

Approximating Capacitated Routing and Delivery Problems. - Prasad Chalasani; Rajeev Motwani 001 (SIAM J. Comput., 1999)

An Online Algorithm for Improving Performance in Navigation. - Avrim Blum; Prasad Chalasani (SIAM J. Comput., 2000)

CAUSE: Learning Granger Causality from Event Sequences using Attribution Methods. - Wei Zhang 058; Thomas Kobber Panum; Somesh Jha; Prasad Chalasani; David Page (ICML, 2020)

Concise Explanations of Neural Networks using Adversarial Training. - Prasad Chalasani; Jiefeng Chen 001; Amrita Roy Chowdhury 001; Xi Wu 001; Somesh Jha (ICML, 2020)

Representation Bayesian Risk Decompositions and Multi-Source Domain Adaptation. - Xi Wu 001; Yang Guo; Jiefeng Chen 001; Yingyu Liang; Somesh Jha; Prasad Chalasani (CoRR, 2020)

MALADE: Orchestration of LLM-powered Agents with Retrieval Augmented Generation for Pharmacovigilance. - Jihye Choi; Nils Palumbo; Prasad Chalasani; Matthew M. Engelhard; Somesh Jha; Anivarya Kumar; David Page (MLHC, 2024)

PolicyLR: A Logic Representation For Privacy Policies. - Ashish Hooda; Rishabh Khandelwal; Prasad Chalasani; Kassem Fawaz; Somesh Jha (CoRR, 2024)

Prεεmpt: Sanitizing Sensitive Prompts for LLMs. - Amrita Roy Chowdhury 001; David Glukhov; Divyam Anshumaan; Prasad Chalasani; Nicolas Papernot; Somesh Jha; Mihir Bellare (CoRR, 2025)