arXiv:2601.08073v1 Announce Type: new Abstract: For a (possibly partial) Boolean function $fcolon{0,1}^nto{0,1}$ as well as a query complexity measure $M$ which maps Boolean functions to real numbers, define the composition limit of $M$ on $f$ by $M^*(f)=lim_{ktoinfty} M(f^k)^{1/k}$. We study the composition limits of general measures in query complexity. We show this limit converges under reasonable assumptions about the measure. We then give a surprising result regarding the composition limit of randomized query complexity: we show $R_0^*(f)=max{R^*(f),C^*(f)}$. Among […]

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arXiv:2603.03587v1 Announce Type: cross Abstract: Method validation and study design in causal inference rely on synthetic data with known counterfactuals. Existing simulators trade off distributional realism, the ability to capture mixed-type and multimodal tabular data, against causal controllability, including explicit control over overlap, unmeasured confounding, and treatment effect heterogeneity. We introduce CausalMix, a variational generative framework that closes this gap by coupling a mixture of Gaussian latent priors with data-type-specific decoders for continuous, binary, and categorical variables. The […]

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By the end of this tutorial, you will clearly understand: Why RL looks similar to supervised learning—but behaves completely differently, Why unsupervised learning is closer philosophically, yet still not the right definition, When RL is the right tool, and when supervised is faster, cheaper, safer, and better, How cost, risk, and feedback shape the correct choice, How hybrid pipelines (Behavioral Cloning (BC) –> RL) work in the real world, How to test your problem using a simple decision […]

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Was Daft Punk Having a Laugh When They Chose the Tempo of Harder, Better, Faster, Stronger? Depending on how you measure it, the tempo of Harder, Better, Faster, Stronger appears to be 123.45 beats per minute. This is one of those things that’s so cool I’m just going to accept it as true. (I only today learned from the Hacker News comments that Veridis Quo is “Very Disco”, and if you flip the order of those words you […]

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This paper addresses binary classification in scenarios where obtaining explicit instance level labels is impractical, by exploiting multiple weak labels defined on instance pairs. The existing SconfConfDiff classification framework relies on continuous valued probabilistic supervision, including similarity-confidence, the probability of class agreement, and confidence-difference, the difference in positive class probabilities. However, probabilistic labeling requires subjective uncertainty quantification, often leading to unstable supervision. We propose SD-Pcomp classification, a binary judgment based weakly supervised learning framework that relies only on […]

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arXiv:2603.25943v1 Announce Type: new Abstract: Enormous fluid antenna systems (E-FAS) have recently emerged as a surface-wave (SW)-enabled architecture that can induce controllable large-scale channel gains through guided electromagnetic routing. This paper develops a secrecy analysis framework for E-FAS-assisted downlink transmission with practical pilot-based channel estimation. We consider a multiple-input single-output (MISO) wiretap setting in which the base station (BS) performs minimum mean-square-error (MMSE) channel estimation and adopts maximum-ratio transmission (MRT) with artificial noise (AN). To capture the leakage […]

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arXiv:2604.16872v1 Announce Type: new Abstract: Large Language Models (LLMs) can be helpful for literature search and summarisation, but retracted articles can confuse them. This article asks three open weights (offline) LLMs whether 161 high profile retracted articles had been retracted, performing a similar check for a benchmark multidisciplinary set of 34,070 non-retracted articles. Based on titles and abstracts, in over 80% of cases the LLMs claimed that a retracted article had not been retracted (GPT OSS 120B: 82%; […]

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arXiv:2601.02363v1 Announce Type: new Abstract: Avatar embodiment experiences have the potential to enhance human capabilities by extending human senses, body, and mind. This study investigates social acceptance of robotic and virtual avatars as enablers of capability enhancement in six domains: identity exploration, well-being and behavioral transformation, expanded travel capabilities, expanded bodily and sensory abilities, cognitive augmentation, and immortality. We conducted a large-scale survey (n = 1001) in Dubai to explore acceptance of sixteen capability enhancement scenarios within these […]

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