8 papers · 1 filter
On Union-Closedness of Language Generation
Steve Hanneke, Amin Karbasi, Anay Mehrotra +1
We investigate language generation in the limit - a model by Kleinberg and Mullainathan [NeurIPS 2024] and extended by Li, Raman, and Tewari [COLT 2025]. While Kleinberg and Mullai…
(Im)possibility of Automated Hallucination Detection in Large Language Models
Amin Karbasi, Omar Montasser, John Sous +1
Is automated hallucination detection possible? In this work, we introduce a theoretical framework to analyze the feasibility of automatically detecting hallucinations produced by l…
Adversarial Reasoning at Jailbreaking Time
Mahdi Sabbaghi, Paul Kassianik, George Pappas +3
As large language models (LLMs) are becoming more capable and widespread, the study of their failure cases is becoming increasingly important. Recent advances in standardizing, mea…
Extracting Memorized Training Data via Decomposition
Ellen Su, Anu Vellore, Amy Chang +4
The widespread use of Large Language Models (LLMs) in society creates new information security challenges for developers, organizations, and end-users alike. LLMs are trained on la…
Injecting Undetectable Backdoors in Obfuscated Neural Networks and Language Models
Alkis Kalavasis, Amin Karbasi, Argyris Oikonomou +3
As ML models become increasingly complex and integral to high-stakes domains such as finance and healthcare, they also become more susceptible to sophisticated adversarial attacks.…
On the Computational Landscape of Replicable Learning
Alkis Kalavasis, Amin Karbasi, Grigoris Velegkas +1
We study computational aspects of algorithmic replicability, a notion of stability introduced by Impagliazzo, Lei, Pitassi, and Sorrell [2022]. Motivated by a recent line of work t…