In the evolving landscape of cybersecurity, the manual and time-consuming process of identifying malware remains a major bottleneck in security analysis. This study presents a novel approach to addressing this challenge by leveraging Natural Language Processing (NLP) techniques. This research focuses on a comparative analysis of two neural networks—a Long Short-Term Memory (LSTM) model and a Transformer model that analyze API call sequences and capture the relationships between API calls. Using a publicly available dataset, the models perform […]

Ver mais

arXiv:2603.24767v1 Announce Type: new Abstract: Systematic reviews traditionally have taken considerable amounts of human time and energy to complete, in part due to the extensive number of titles and abstracts that must be reviewed for potential inclusion. Recently, researchers have begun to explore how to use large language models (LLMs) to make this process more efficient. However, research to date has shown inconsistent results. We posit this is because prompting alone may not provide sufficient context for the […]

Ver mais

arXiv:2602.22395v1 Announce Type: new Abstract: Since 2016, the term “misinformation” has become associated with a scientific paradigm that studies, at its core, people making, reading, and sharing false statements, usually on social media, and often warning of the harm to society resulting from the sum of many such events. By tracking the term through the academic literature, with special focus on the years 2011–2023, we connect the post-2016 paradigm with a strand of research dating to the Satanic […]

Ver mais

Hihg-temperature creep characterization of structural alloys traditionally relies on serial uniaxial tests, which are highly inefficient for exploring the large search space of alloy compositions and for material discovery. Here, we introduce a machine-learning-assisted, high-throughput framework for creep law identification based on a dimple array bulge instrument (DABI) configuration, which enables parallel creep testing of 25 dimples, each fabricated from a different alloy, in a single experiment. Full-field surface displacements of dimples undergoing time-dependent creep-induced bulging under inert […]

Ver mais

arXiv:2407.02357v3 Announce Type: replace-cross Abstract: In recent years, there has been growing interest in jointly analyzing a foreground dataset, representing an experimental group, and a background dataset, representing a control group. The goal of such contrastive investigations is to identify salient features in the experimental group relative to the control. Independent component analysis (ICA) is a powerful tool for learning independent patterns in a dataset. We generalize it to contrastive ICA (cICA). For this purpose, we devise a […]

Ver mais

arXiv:2603.03488v1 Announce Type: new Abstract: Given a graph, when can we orient the edges to satisfy local constraints at the vertices, where each vertex specifies which local orientations of its incident edges are allowed? This family of graph orientation problems is a special kind of SAT problem, where each variable (edge orientation) appears in exactly two clauses (vertex constraints) — once positively and once negatively. We analyze the complexity of many natural vertex types (patterns of allowed vertex […]

Ver mais

Hello! I am looking for research that has successfully applied AlphaZero/MuZero-style learning to sequential, perfect information, non-zero sum board games, e.g. Terra Mystica where the winning player is decided by a numerical score (associated with each player) at the end of the game, rather than the zero sum outcomes of games such as Chess, Shogi, Go, etc. I figure there must exist an approach that works for multi-agent (> 2 player) games. Any suggestions? Thank you submitted by […]

Ver mais

arXiv:2503.18896v2 Announce Type: replace-cross Abstract: A statistical model is said to be calibrated if the resulting mean estimates perfectly match the true means of the underlying responses. Aiming for calibration is often not achievable in practice as one has to deal with finite samples of noisy observations. A weaker notion of calibration is auto-calibration. An auto-calibrated model satisfies that the expected value of the responses for a given mean estimate matches this estimate. Testing for autocalibration has only […]

Ver mais

A zero knowledge proof (ZKP) answers a question without revealing anything more than answer. For example, a digital signature proves your possession of a private key without revealing that key. Here’s another example, one that’s more concrete than a digital signature. Suppose you have a deck of 52 cards, 13 of each of spades, hearts, diamonds, and clubs. If I draw a spade from the deck, I can prove that I drew a spade without showing which card […]

Ver mais