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3,113 papers
This teaching companion accompanies Chapter 8, Authorship Attribution in Arabic: From Stylometric Methods to Large Language Models, prepared for the edited volume Arabic Digital Humanities (John Benjamins). It provides an illustrated teaching guide, Python and R scripts, fixed evaluation folds, corpus and excerpt manif...
Machine-learning intrusion detectors reach high average accuracy yet fail consistently on a small set of flows near the decision boundary, where benign and attack traffic overlap in feature space. These errors matter operationally, and standard remedies stop short: adversarial training adds perturbations whose gradient...
Financial institutions want to read the narrative of markets with language models, but much of what matters most — internal research, positions, committee notes, client communications — cannot leave their perimeter. This report describes how Epistemic Symmetry Theory (EST), a framework that detects regime changes in ma...
Autonomous vehicle (AV) crashes continue to occur, indicating the need for a comprehensive understanding of their characteristics to support safety management in future mixed-traffic environments. Previous studies employing text mining or rule extraction have faced limitations in generalizing findings due to small, het...
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Background-Science and social studies (IPAS) at SDN Kampung Bulak 01 relied on textbooks and teacher-centered explanations, limiting contextual cultural engagement and the development of nationalist attitudes. Objectives-This study aimed to develop and evaluate an Augmented Reality (AR)-based comic learning media for f...
This dataset contains 148 questionnaire response records on AI use, cognitive offloading, and academic stress among university students. Prepared for a thesis on AI dependency and academic stress, it provides 43 variables for analysis and exploratory machine learning. Each row is one response. Responses were collected...
Abstract We develop a Hamiltonian N-Space framework in which physical space is modeled as a static granular substrate endowed with a network capable of transporting spectrally distributed energy. Energy transport through this network defines a spectral flux. Persistent localized configurations of spectral energy are de...
Language model services count, limit and bill text in tokens, but the number of tokens needed for the same content depends on the language and on the tokenizer. We measure this token ratio relative to English for the 23 non-English official languages of the European Union on nine tokenizers of 2026: six company tokeniz...
Network Intrusion Detection Systems (NIDSs) based on machine learning have demonstrated strong performance against known attack patterns. However, their robustness against adaptive evasion strategies orchestrated by modern Large Language Models (LLMs) remains largely unexplored. This study presents a reproducible frame...
Locally run small language models enable generating SQL from natural language without sending the database schema to third-party servers. However, a model fine-tuned only to "translate the question into SQL" can also translate destructive or unauthorized commands embedded in the prompt. In this report we measure, under...
The findings support use of LLMs in endodontic diagnosis and treatment planning as adjunctive tools, but not without expert supervision, and performance was endpoint-specific and substantially reduced on integrated assessment and low-prevalence categories.
A ReAct-style agent accumulates observations, intermediate results, and failed attempts in a single context. As this context grows, stale and off-path information consumes its limited capacity and obscures relevant evidence, making focused reasoning increasingly difficult. We introduce TreeFlex, a framework in which th...
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
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