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Quantum entanglement is a fundamental property of quantum mechanics and plays a crucial role in quantum computation and information. We study entanglement via the lens of computational complexity by considering quantum generalizations of…

Quantum Physics · Physics 2024-03-01 Fernando Granha Jeronimo , Pei Wu

Large Language Models (LLMs) as stochastic systems may generate numbers that deviate from available data, a failure known as \emph{numeric hallucination}. Existing safeguards -- retrieval-augmented generation, citations, and uncertainty…

Computation and Language · Computer Science 2025-09-09 Aivin V. Solatorio

Reactive systems are composed of a well defined set of input events that the system reacts with by executing an associated handler to each event. In concurrent environments, event handlers can interact with the execution of other programs…

Software Engineering · Computer Science 2018-10-19 Yongwang Zhao , David Sanan , Fuyuan Zhang , Yang Liu

Model Context Protocol (MCP) is a rapidly adopted standard for defining and invoking external tools in LLM applications. The multi-layered architecture of MCP introduces new attack surfaces such as tool poisoning, in addition to traditional…

Cryptography and Security · Computer Science 2026-04-21 İpek Abasıkeleş Turgut , Edip Gümüş

Motivated by the fact that input distributions are often unknown in advance, distribution-free property testing considers a setting where the algorithmic task is to accept functions $f : [n] \to \{0,1\}$ with a certain property P and reject…

Computational Complexity · Computer Science 2024-02-19 Hugo Aaronson , Tom Gur , Ninad Rajgopal , Ron D. Rothblum

Secure communication in the Multi-user and Multi-eavesdropper (MUME) scenario is considered in this paper. It has be shown that secrecy can be improved when the transmitter simultaneously transmits information-bearing signal to the intended…

Information Theory · Computer Science 2020-03-25 Kun Xie , Wen Chen , Lili Wei

Vulnerability of Frontier language models to misuse and jailbreaks has prompted the development of safety measures like filters and alignment training in an effort to ensure safety through robustness to adversarially crafted prompts. We…

Cryptography and Security · Computer Science 2024-10-31 David Glukhov , Ziwen Han , Ilia Shumailov , Vardan Papyan , Nicolas Papernot

A promising approach to defend against side channel attacks is to build programs that are leakage resilient, in a formal sense. One such formal notion of leakage resilience is the n-threshold-probing model proposed in the seminal work by…

Cryptography and Security · Computer Science 2016-10-31 Arthur Blot , Masaki Yamamoto , Tachio Terauchi

Data attribution methods aim to answer useful counterfactual questions like "what would a ML model's prediction be if it were trained on a different dataset?" However, estimation of data attribution models through techniques like empirical…

Machine Learning · Computer Science 2025-08-19 Ari Karchmer , Martin Pawelczyk , Seth Neel

This paper introduces a run-time mechanism for preventing leakage of secure information in distributed systems. We consider a general concurrency language model, where concurrent objects interact by asynchronous method calls and futures.…

Programming Languages · Computer Science 2020-02-26 Farzane Karami , Olaf Owe , Gerardo Schneider

Multiparty session types (MP) are a type discipline for enforcing the structured, deadlock-free communication of concurrent and message-passing programs. Traditional MP have a limited form of choice in which alternative communication…

Logic in Computer Science · Computer Science 2024-06-10 Kirstin Peters , Nobuko Yoshida

We study privacy guarantees in the framework of pointwise maximal leakage (PML) that satisfy two requirements: they are robust under post-processing and upper bound the failure probability, i.e., the probability that the information leakage…

Cryptography and Security · Computer Science 2026-05-21 Sara Saeidian , Carlos Pinzón , Catuscia Palamidessi

We introduce the notion of \emph{traceable mixnets}. In a traditional mixnet, multiple mix-servers jointly permute and decrypt a list of ciphertexts to produce a list of plaintexts, along with a proof of correctness, such that the…

Cryptography and Security · Computer Science 2024-06-25 Prashant Agrawal , Abhinav Nakarmi , Mahavir Prasad Jhawar , Subodh Sharma , Subhashis Banerjee

Chain-of-Thought (CoT) prompting improves LLM reasoning but can increase privacy risk by resurfacing personally identifiable information (PII) from the prompt into reasoning traces and outputs, even under policies that instruct the model…

Computation and Language · Computer Science 2026-03-09 Patrick Ahrend , Tobias Eder , Xiyang Yang , Zhiyi Pan , Georg Groh

Understanding how information can efficiently spread in distributed systems under noisy communications is a fundamental question in both biological research and artificial system design. When agents are able to control whom they interact…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-11-11 Niccolò D'Archivio , Amos Korman , Emanuele Natale , Robin Vacus

The study of distributed interactive proofs was initiated by Kol, Oshman, and Saxena [PODC 2018] as a generalization of distributed decision mechanisms (proof-labeling schemes, etc.), and has received a lot of attention in recent years. In…

Quantum Physics · Physics 2023-12-29 François Le Gall , Masayuki Miyamoto , Harumichi Nishimura

In multi-cast scenario, all desired users are divided into $K$ groups. Each group receives its own individual confidential message stream. Eavesdropper group aims to intercept $K$ confidential-message streams. To achieve a secure…

Information Theory · Computer Science 2017-12-29 Feng Shu , Ling Xu , Jiangzhou Wang , Wei Zhu , Zhou Xiaobo

How much adversarial noise can protocols for interactive communication tolerate? This question was examined by Braverman and Rao (IEEE Trans. Inf. Theory, 2014) for the case of "robust" protocols, where each party sends messages only in…

Data Structures and Algorithms · Computer Science 2015-08-10 Shweta Agrawal , Ran Gelles , Amit Sahai

Due to their weak inductive bias, Multi-Layer Perceptrons (MLPs) have subpar performance at low-compute levels compared to standard architectures such as convolution-based networks (CNN). Recent work, however, has shown that the performance…

Machine Learning · Computer Science 2024-10-15 Sean Wu , Jordan Hong , Keyu Bai , Gregor Bachmann

We study a notion of robustness of a Markov kernel that describes a system of several input random variables and one output random variable. Robustness requires that the behaviour of the system does not change if one or several of the input…

Probability · Mathematics 2014-06-18 Johannes Rauh , Nihat Ay
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