3 papers
cs.CR2026
Engineering Robustness into Personal Agents with the AI Workflow Store
Roxana Geambasu, Mariana Raykova, Pierre Tholoniat +3
The dominant paradigm for AI agents is an "on-the-fly" loop in which agents synthesize plans and execute actions within seconds or minutes in response to user prompts. We argue tha…
cs.LG2026
A Prior-Aware Metric for Efficiently Distinguishing Memorization from Generalization in Large Language Models
Trishita Tiwari, Ari Trachtenberg, G. Edward Suh
Training data leakage from Large Language Models (LLMs) raises serious concerns related to privacy, security, and copyright compliance. A central challenge in assessing this risk i…
cs.CL2025
Sequence-Level Leakage Risk of Training Data in Large Language Models
Trishita Tiwari, G. Edward Suh
This work quantifies the risk of training data leakage from LLMs (Large Language Models) using sequence-level probabilities. Computing extraction probabilities for individual seque…