technocracy

arXiv:2601.07984v1 Announce Type: new Abstract: Vision-Language Models (VLMs) excel at visual perception, yet their ability to interpret cultural meaning in art remains under-validated. We present a tri-tier evaluation framework for cross-cultural art-critique assessment: Tier I computes automated coverage and risk indicators offline; Tier II applies rubric-based scoring using a single primary judge across five dimensions; and Tier III calibrates the Tier II aggregate score to human ratings via isotonic regression, yielding a 5.2% reduction in MAE on a […]

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arXiv:2603.08825v1 Announce Type: new Abstract: Discrete graph generation has emerged as a powerful paradigm for modeling graph data, often relying on highly expressive neural backbones such as transformers or higher-order architectures. We revisit this design choice by introducing GenGNN, a modular message-passing framework for graph generation. Diffusion models with GenGNN achieve more than 90% validity on Tree and Planar datasets, within margins of graph transformers, at 2-5x faster inference speed. For molecule generation, DiGress with a GenGNN backbone […]

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South by Southwest 2026 hosts a remarkable concentration of awards ceremonies across audio, film, television, and digital culture. This guide covers the three major podcasting award events in detail: the 2026 iHeartPodcast Awards, the inaugural Independent Podcast and Creator Awards (Indie PaC Awards), the SXSW Film & TV Awards, each distinct in format, eligibility, and what they recognize. The SXSW Awards Schedule Fri–Sat, March 13–14: SXSW Pitch : Startup showcase across nine categories, a live audience and a […]

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arXiv:2601.15496v1 Announce Type: new Abstract: In this paper, we study the timeliness of actions in communication systems where actuation is constrained by control permissions or energy availability. Building on the Age of Actuation (AoA) metric, which quantifies the timeliness of actions independently of data freshness, we introduce a new metric, the emph{Age of Actuated Information (AoAI)}. AoAI captures the end-to-end timeliness of actions by explicitly accounting for the age of the data packet at the moment it is […]

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Predictive confidence serves as a foundational control signal in mission-critical systems, directly governing risk-aware logic such as escalation, abstention, and conservative fallback. While prior federated learning attacks predominantly target accuracy or implant backdoors, we identify confidence calibration as a distinct attack objective. We present the Temperature Scaling Attack (TSA), a training-time attack that degrades calibration while preserving accuracy. By injecting temperature scaling with learning rate-temperature coupling during local training, malicious updates maintain benign-like optimization behavior, evading accuracy-based monitoring […]

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I recently submitted Nullmail to Proof of Usefulness, and it scored +76 – officially “in business”! Here’s why this project matters. What It Is Nullmail is a verifiable, open-source privacy tool with active development and organic traction. While early-stage (approx. 10,000 monthly inboxes), the project’s ‘privacy-first’ architecture is validated by its open GitHub repository and recent ‘battle-testing’ against domain flagging (Cloudflare). It effectively solves a specific problem (disposable email) without data collection, positioning it as a high-utility tool […]

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We study partial-feedback online learning, where each instance admits a set of correct labels, but the learner only observes one correct label per round; any prediction within the correct set is counted as correct. This model captures settings such as language generation, where multiple responses may be valid but data provide only a single reference. We give a near-complete characterization of minimax regret for both deterministic and randomized learners in the set-realizable regime, i.e., in the regime where […]

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arXiv:2604.07382v1 Announce Type: new Abstract: The geometric structure of latent representations in large language models (LLMs) is an active area of research, driven in part by its implications for model transparency and AI safety. Existing literature has focused mainly on general geometric and topological properties of the learnt representations, but due to a lack of ground-truth latent geometry, validating the findings of such approaches is challenging. Emotion processing provides an intriguing testbed for probing representational geometry, as emotions […]

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arXiv:2601.04211v1 Announce Type: new Abstract: We present Qwerty AI, an end-to-end system for automated age-rating and content-safety assessment of Russian-language screenplays according to Federal Law No. 436-FZ. The system processes full-length scripts (up to 700 pages in under 2 minutes), segments them into narrative units, detects content violations across five categories (violence, sexual content, profanity, substances, frightening elements), and assigns age ratings (0+, 6+, 12+, 16+, 18+) with explainable justifications. Our implementation leverages a fine-tuned Phi-3-mini model with […]

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