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arXiv:2604.15316v1 Announce Type: new Abstract: With large language models (LLMs) becoming increasingly prevalent in daily life, so too has the tendency to attribute to them human-like minds and emotions, or anthropomorphize them. Here, we investigate dimensions people use to anthropomorphize and attribute trust toward LLMs across more than 2,000 human-LLM interactions. Participants (N=115) engaged with LLM chatbots systematically varied in warmth (friendliness), competence (capability, coherence), and empathy (cognitive and affective). Warmth and cognitive empathy significantly predicted perceptions on […]

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arXiv:2604.15315v1 Announce Type: new Abstract: Consider a two-player game repeated N times. Player 1 can choose between two styles (for interpretability, offensive and defensive), whereas Player 2 uses a single fixed style. Let X N,:= #wins -#losses for Player 1 after N games, and define the match gain as E[sign(X N )], with sign(0) = 0. We assume Player 1 is weaker in the sense that each pure style is losing in expectation. Our objective is to identify […]

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arXiv:2604.15314v1 Announce Type: new Abstract: This research aimed to develop an intelligent system to evaluate performance and extract behavioral models for children with ASD and neurotypical (TD) children by interacting with a virtual social robot in a music education program using deep neural networks. The system has two main features: 1) it distinguishes between neurotypical children and those with ASD based on their behavior, and 2) generates behaviors resembling those of neurotypical or ASD children in similar situations […]

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Vercel powers more than 4 million websites and processes 30 billion requests every week. That scale makes it an attractive target. On April 19, 2026, a ShinyHunters-affiliated threat actor claimed a breach of Vercel’s internal systems not by attacking Vercel’s platform directly, but by stealing OAuth credentials from a third-party AI tool connected to Vercel’s Google Workspace. The attacker is now demanding a $2 million ransom and has listed the alleged data on BreachForums. This article breaks down […]

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Data scarcity remains a fundamental bottleneck in applying deep learning to wireless communication problems, particularly in scenarios where collecting labeled Radio Frequency (RF) data is expensive, time-consuming, or operationally constrained. This paper proposes LLM-AUG, a data augmentation framework that leverages in-context learning in large language models (LLMs) to generate synthetic training samples directly in a learned embedding space. Unlike conventional generative approaches that require training task-specific models, LLM-AUG performs data generation through structured prompting, enabling rapid adaptation in […]

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Hello everyone! I’ve been independently researching & developing small-but-powerful vision-language models (VLMs) and noticed a gap in visual datasets – none were teaching my model to simply ground text in imagery, but trying to get it to reason about the text or about the scene itself. This lead me down a 2 week side-side-project to create SGOCR, an open source dataset pipeline for generating spatially-grounded, OCR-focused VQA tuples with tons of rich metadata to support diverse VLM training […]

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