arXiv subjects

Manuel Goulão

Publications and source records attributed to Manuel Goulão.

8 recordsLinked to original sources

arXiv2026

Computational Cryptography from Pseudoentanglement

The advent of pseudoentanglement and computational entanglement theory bootstrapped a wave of research at the intersection of computer science and information theory. In parallel, computational cryptography has undergone substantial development, prompted by the introduction of pseudorandom states and followed by the establishment of a baseline for the computational hardness required for quantum cryptography, from which EFI pairs emerge as a central primitive. We study the connection between pseudoentanglement and computational cryptography through EFI pairs. Our goal is to enable the use of resources arising from computational entanglement theory in the field of cryptography. For this, we establish the relation between operational instances of pseudoentanglement and the hierarchy of minimal assumptions for computational cryptography. We show that the existence of pseudoentanglement under two different operational definitions, with efficient state generation, is a sufficient condition for the existence of EFI pairs. Combined with a previously established result that the converse also holds under the second definition, this allows us to also demonstrate their equivalence. This places pseudoentanglement alongside other minimal assumptions in cryptography, not only offering an alternative perspective on this fundamental problem, but also building a bridge that allows insights from either area to inform the other. While proving these theorems, we introduce and demonstrate technical lemmas in quantum information and computational entanglement theory, relating the computational entanglement measures to the distance between states, establishing distinguishing conditions for mixtures of two families given pairwise distances between their states, and demonstrating the first continuity relation for a computational entanglement measure.

quant-ph↗

arXiv2026

CommonLID: Re-evaluating State-of-the-Art Language Identification Performance on Web Data

Language identification (LID) is a fundamental step in curating multilingual corpora. However, LID models still perform poorly for many languages, especially on the noisy and heterogeneous web data often used to train multilingual language models. In this paper, we introduce CommonLID, a community-driven, human-annotated LID benchmark for the web domain, covering 109 languages. Many of the included languages have been previously under-served, making CommonLID a key resource for developing more representative high-quality text corpora. We show CommonLID's value by using it, alongside five other common evaluation sets, to test eight popular LID models. We analyse our results to situate our contribution and to provide an overview of the state of the art. In particular, we highlight that existing evaluations overestimate LID accuracy for many languages in the web domain. We make CommonLID and the code used to create it available under an open, permissive license.

cs.CL↗

arXiv2025

Gymnasium: A Standard Interface for Reinforcement Learning Environments

Reinforcement Learning (RL) is a continuously growing field that has the potential to revolutionize many areas of artificial intelligence. However, despite its promise, RL research is often hindered by the lack of standardization in environment and algorithm implementations. This makes it difficult for researchers to compare and build upon each other's work, slowing down progress in the field. Gymnasium is an open-source library that provides a standard API for RL environments, aiming to tackle this issue. Gymnasium's main feature is a set of abstractions that allow for wide interoperability between environments and training algorithms, making it easier for researchers to develop and test RL algorithms. In addition, Gymnasium provides a collection of easy-to-use environments, tools for easily customizing environments, and tools to ensure the reproducibility and robustness of RL research. Through this unified framework, Gymnasium significantly streamlines the process of developing and testing RL algorithms, enabling researchers to focus more on innovation and less on implementation details. By providing a standardized platform for RL research, Gymnasium helps to drive forward the field of reinforcement learning and unlock its full potential. Gymnasium is available online at https://github.com/Farama-Foundation/Gymnasium

cs.LG↗

arXiv2025

Performance of Practical Quantum Oblivious Key Distribution

Motivated by the applications of secure multiparty computation as a privacy-protecting data analysis tool, and identifying oblivious transfer as one of its main practical enablers, we propose a practical realization of randomized quantum oblivious transfer. By using only symmetric cryptography primitives to implement commitments, we construct computationally-secure randomized oblivious transfer without the need for public-key cryptography or assumptions imposing limitations on the adversarial devices. We show that the protocol is secure under an indistinguishability-based notion of security and demonstrate an experimental implementation to test its real-world performance. Its security and performance are then compared to both quantum and classical alternatives, showing potential advantages over existing solutions based on the noisy storage model and public-key cryptography.

quant-ph↗

arXiv2025

Non-Interactive Oblivious Transfer and One-Time Programs from Noisy Quantum Storage

Few primitives are as intertwined with the foundations of cryptography as Oblivious Transfer (OT). Not surprisingly, with the advent of quantum information processing, a major research path has emerged, aiming to minimize the requirements necessary to achieve OT by leveraging quantum resources, while also exploring the implications for secure computation. Indeed, OT has been the target of renewed focus regarding its newfound quantum possibilities (and impossibilities), both towards its computation and communication complexity. For instance, non-interactive OT, known to be impossible classically, has been strongly pursued. In its most extreme form, non-interactive chosen-input OT (one-shot OT) is equivalent to a One-Time Memory (OTM). OTMs have been proposed as tamper-proof hardware solutions for constructing One-Time Programs -- single-use programs that execute on an arbitrary input without revealing anything about their internal workings. In this work, we leverage quantum resources in the Noisy-Quantum-Storage Model to achieve: 1. Unconditionally-secure two-message non-interactive OT -- the smallest number of messages known to date for unconditionally-secure chosen-input OT. 2. Computationally-secure one-shot OT/OTM, with everlasting security, assuming only one-way functions and sequential functions -- without requiring trusted hardware, QROM, or pre-shared entanglement. 3. One-Time Programs without the need for hardware-based solutions or QROM, by compiling our OTM construction with the [GKR08, GIS+10] compiler.

quant-ph↗

arXiv2024

Pseudo-Entanglement is Necessary for EFI Pairs

Regarding minimal assumptions, most of classical cryptography is known to depend on the existence of One-Way Functions (OWFs). However, recent evidence has shown that this is not the case when considering quantum resources. Besides the well known unconditional security of Quantum Key Distribution, it is now known that computational cryptography may be built on weaker primitives than OWFs, e.g., pseudo-random states [JLS18], one-way state generators [MY23], or EFI pairs of states [BCQ23]. We consider a new quantum resource, pseudo-entanglement, and show that the existence of EFI pairs, one of the current main candidates for the weakest computational assumption for cryptography (necessary for commitments, oblivious transfer, secure multi-party computation, computational zero-knowledge proofs), implies the existence of pseudo-entanglement, as defined by [ABF+24, ABV23] under some reasonable adaptations. We prove this by constructing a new family of pseudo-entangled quantum states given only EFI pairs. Our result has important implications for the field of computational cryptography. It shows that if pseudo-entanglement does not exist, then most of cryptography cannot exist either. Moreover, it establishes pseudo-entanglement as a new minimal assumption for most of computational cryptography, which may pave the way for the unification of other assumptions into a single primitive. Finally, pseudo-entanglement connects physical phenomena and efficient computation, thus, our result strengthens the connection between cryptography and the physical world.

quant-ph↗

arXiv2023

Pretraining the Vision Transformer using self-supervised methods for vision based Deep Reinforcement Learning

The Vision Transformer architecture has shown to be competitive in the computer vision (CV) space where it has dethroned convolution-based networks in several benchmarks. Nevertheless, convolutional neural networks (CNN) remain the preferential architecture for the representation module in reinforcement learning. In this work, we study pretraining a Vision Transformer using several state-of-the-art self-supervised methods and assess the quality of the learned representations. To show the importance of the temporal dimension in this context we propose an extension of VICReg to better capture temporal relations between observations by adding a temporal order verification task. Our results show that all methods are effective in learning useful representations and avoiding representational collapse for observations from Atari Learning Environment (ALE) which leads to improvements in data efficiency when we evaluated in reinforcement learning (RL). Moreover, the encoder pretrained with the temporal order verification task shows the best results across all experiments, with richer representations, more focused attention maps and sparser representation vectors throughout the layers of the encoder, which shows the importance of exploring such similarity dimension. With this work, we hope to provide some insights into the representations learned by ViT during a self-supervised pretraining with observations from RL environments and which properties arise in the representations that lead to the best-performing agents. The source code will be available at: https://github.com/mgoulao/TOV-VICReg

cs.LG↗

arXiv2021

Device-independent quantum authorization based on the Clauser-Horne-Shimony-Holt game

In the spirit of device-independent cryptography, we present a two-party quantum authorization primitive with non-locality as its fueling resource. Therein, users are attributed authorization levels granting them access to a private database accordingly. The authorization levels are encoded in the non-local resources distributed to the users, and subsequently confirmed by their ability to win CHSH games using such resources. We formalize the protocol, prove its security, and frame it in the device-independent setting employing the notion of CHSH self-testing via simulation. Finally, we provide a proof-of-concept implementation using the Qiskit open-source framework.

quant-ph↗