technocracy

Counterfactual explanations (CFs) are increasingly integrated into Machine Learning as a Service (MLaaS) systems to improve transparency; however, ML models deployed via APIs are already vulnerable to privacy attacks such as membership inference and model extraction, and the impact of explanations on this threat landscape remains insufficiently understood. In this work, we focus on the problem of how CFs expand the attack surface of MLaaS by strengthening membership inference attacks (MIAs), and on the need to design defense […]

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STEM education researchers are often interested in identifying moments of students’ mechanistic reasoning for deeper analysis, but have limited capacity to search through many team conversation transcripts to find segments with a high concentration of such reasoning. We offer a solution in the form of an interpretable machine learning model that outputs time-varying probabilities that individual students are engaging in acts of mechanistic reasoning, leveraging evidence from their own utterances as well as contributions from the rest of […]

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arXiv:2602.23464v1 Announce Type: new Abstract: Multi-scalar multiplication (MSM), defined as MSM(P, x) = sum_{i=1}^n x_i P_i, is a dominant computational kernel in discrete-logarithm-based cryptography and often becomes a bottleneck for verifiers and other resource-constrained clients. We present 2G2T, a simple protocol for verifiably outsourcing MSM to an untrusted server. After a one-time keyed setup for fixed bases P = (P1, …, Pn) that produces a public merged-bases vector T and client secret state, the server answers each query […]

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José Argüelles envisions humanity’s next evolutionary leap—a conscious planet where mind and nature merge into a single living intelligence. Blending mysticism, science, and cosmic ecology, he declares that the noosphere—the thinking layer of Earth—is awakening, urging us to replace mechanized time with harmony, art, and planetary awareness before civilization’s final turning point.

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Detecting out-of-distribution (OOD) graphs is crucial for ensuring the safety and reliability of Graph Neural Networks. In unsupervised graph-level OOD detection, models are typically trained using only in-distribution (ID) data, resulting in incomplete feature space characterization and weak decision boundaries. Although synthesizing outliers offers a promising solution, existing approaches rely on fixed, non-adaptive sampling heuristics (e.g., distance- or density-based), limiting their ability to explore informative OOD regions. We propose a Policy-Guided Outlier Synthesis (PGOS) framework that replaces static […]

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arXiv:2602.16752v1 Announce Type: new Abstract: Large Language Models (LLMs) have emerged as powerful re-rankers. Recent research has however showed that simple prompt injections embedded within a candidate document (i.e., jailbreak prompt attacks) can significantly alter an LLM’s ranking decisions. While this poses serious security risks to LLM-based ranking pipelines, the extent to which this vulnerability persists across diverse LLM families, architectures, and settings remains largely under-explored. In this paper, we present a comprehensive empirical study of jailbreak prompt […]

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arXiv:2508.11847v3 Announce Type: replace Abstract: We propose a method for evaluating the robustness of widely used LLM ranking systems — variants of a Bradley–Terry model — to dropping a worst-case very small fraction of preference data. Our approach is computationally fast and easy to adopt. When we apply our method to matchups from popular LLM ranking platforms, including Chatbot Arena and derivatives, we find that the rankings of top-performing models can be remarkably sensitive to the removal of […]

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Introduction: The Cost Illusion AI agents look cheap and powerful at first. You send one request and get a smart answer. They can write emails, search information, automate tasks, and even make decisions. In demos, everything feels fast, simple, and scalable. But that is not how they actually work. What looks like one request is usually many steps happening behind the scenes. The agent does not just respond. It breaks the task down, decides what to do, tries […]

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arXiv:2604.18814v1 Announce Type: new Abstract: An algorithm for simulation of switching converters is proposed in the paper. The algorithm is based on simulation of averaged circuit model applying “switching cell” concept, and construction of instantaneous values of the waveforms using quasi steady state and linear ripple approximation. Simulation covers converters operating both in the continuous and the discontinuous conduction mode. Application of the algorithm is demonstrated by simulation results of all three of the basic converters: buck, boost […]

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Long before “engineering” became a formal career path, it was already part of Will Jiang’s daily life. Growing up in China, Jiang was the student teacher whom a classmate turned to when a laptop froze minutes before class. By high school, he was maintaining his school’s network infrastructure by diagnosing connectivity issues, keeping systems online, and supporting hundreds of users. What stayed with him wasn’t just the technical challenge, but the idea that thoughtfully built systems could quietly […]

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