collaborators

5 papers

cs.AR2026

Formal-Verification-Guided Bayesian Optimization for Non-Intrusive Last-Mile Coverage Closure

Chengjia Liu, Priyadarsi Mishra, David Kebo Houngninou +3

Last-mile functional coverage closure for modern chip designs remains costly because a mature UVM environment exposes many controls while direct hits on the remaining bins are spar…

cs.AI2026

When Pleasing the User Compromises Care: AI Sycophancy in Caregiver-Mediated Healthcare

Priyadarsi Mishra, Arjun Beniwal, Ziyu Yi +2

Large language model (LLM) alignment often assumes that the user interacting with a model is also the primary beneficiary of its behavior. Yet in many consequential settings, one p…

cs.AI2026

Distribution-Aware Programming: Learning Specialized Solvers from Experience

Saharsh Koganti, Priyadarsi Mishra, Pierfrancesco Beneventano +1

Many optimization problems are solved repeatedly on instances drawn from the same underlying distribution. In this setting, a system can begin with a general-purpose solver and use…

cs.LG2025

On the Alignment Between Supervised and Self-Supervised Contrastive Learning

Achleshwar Luthra, Priyadarsi Mishra, Tomer Galanti

Self-supervised contrastive learning (CL) has achieved remarkable empirical success, often producing representations that rival supervised pre-training on downstream tasks. Recent…

cs.LG2025

LLM Priors for ERM over Programs

Shivam Singhal, Priyadarsi Mishra, Eran Malach +1

We study program-learning methods that are efficient in both samples and computation. Classical learning theory suggests that when the target admits a short program description, fo…