This study explores the application of autoencoder-based machine learning techniques for anomaly detection to identify exoplanet atmospheres with unconventional chemical signatures using a low-dimensional data representation. We use the Atmospheric Big Challenge (ABC) database, a publicly available dataset with over 100,000 simulated exoplanet spectra, to construct an anomaly detection scenario by defining CO2-rich atmospheres as anomalies and CO2-poor atmospheres as the normal class. We benchmarked four different anomaly detection strategies: Autoencoder Reconstruction Loss, One-Class Support Vector Machine (1 […]

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OpenAI is updating its Model Spec with new Under-18 Principles that define how ChatGPT should support teens with safe, age-appropriate guidance grounded in developmental science. The update strengthens guardrails, clarifies expected model behavior in higher-risk situations, and builds on our broader work to improve teen safety across ChatGPT.

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We propose DeePM (Deep Portfolio Manager), a structured deep-learning macro portfolio manager trained end-to-end to maximize a robust, risk-adjusted utility. DeePM addresses three fundamental challenges in financial learning: (1) it resolves the asynchronous "ragged filtration" problem via a Directed Delay (Causal Sieve) mechanism that prioritizes causal impulse-response learning over information freshness; (2) it combats low signal-to-noise ratios via a Macroeconomic Graph Prior, regularizing cross-asset dependence according to economic first principles; and (3) it optimizes a distributionally robust objective […]

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I’m looking for hands-on resources (courses, repos, playlists) that actually train agents from pixels, not just theory.I am thinking to buy this course on udemy Advanced AI: Deep Reinforcement Learning in PyTorch (v2). Is there any better free alternative. Anyone experienced guide me on this to go from zero → building autonomous agents? submitted by /u/These_Negotiation936 [link] [comments]

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In 2026, community commerce is no longer a niche experiment—it’s a central strategy for brands that want to thrive in a world dominated by Gen Z, social platforms, and user-generated content (UGC). Unlike traditional e-commerce, which treats customers as transactions, community commerce treats them as collaborators, advocates, and co-creators. It’s where trust, shared identity, and real conversations drive sales—not just ads or discount codes. At its core, community commerce is a relationship model. Brands that master it flip […]

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arXiv:2601.02364v1 Announce Type: new Abstract: Traditional recommender systems (RS) have been primarily optimized for accuracy and short-term engagement, often overlooking transparency and trustworthiness. Recently, platforms such as Amazon and Instagram have begun providing recommendation rationales to users, acknowledging their critical role in fostering trust and enhancing engagement; however, most existing systems still treat them as post-hoc artifacts. We propose an LLM-based recommender (LLM-Rec) that not only predicts items but also generates logically grounded rationales. Our approach leverages a […]

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arXiv:2601.00001v1 Announce Type: new Abstract: Hospitals are among the most cognitively demanding indoor environments, especially for patients and visitors unfamiliar with their layout. This study investigates the effectiveness of an augmented reality (AR)-based handheld navigation system compared to traditional paper maps in a large hospital setting. Through a mixed-methods experiment with 32 participants, we measured navigation performance, cognitive workload (NASA-TLX), situational anxiety (STAI-State), spatial behavior, and user satisfaction. Results show that AR users completed navigation tasks significantly faster, […]

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arXiv:2601.02390v1 Announce Type: new Abstract: We make modifications to the unscented Kalman filter (UKF) which bestow almost complete practical identifiability upon a lumped-parameter cardiovascular model with 10 parameters and 4 output observables – a highly non-linear, stiff problem of clinical significance. The modifications overcome the challenging problems of rank deficiency when applying the UKF to parameter estimation. Rank deficiency usually means only a small subset of parameters can be estimated. Traditionally, pragmatic compromises are made, such as selecting […]

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Executive Summary I spent four weeks part-time (probably 80 hours total) building a complete reactive UI framework with 40+ components, a router, and supporting interactive website using only LLM-generated code, it is evident LLMs can produce quality code—but like human developers, they need the right guidance. Key Findings On Code Quality: Well-specified tasks yield clean first-pass code Poorly specified or unique requirements produce sloppy implementations Code degrades over time without deliberate refactoring LLMs defensively over-engineer when asked to […]

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