Market Prediction Despite the recent backlash around WLFI, political memecoins connected to the Trump family are likely to be among the most impactful assets in the next 2-3 years. After years in the crypto industry, you start recognizing patterns not just in the token charts, but also in the behavior of traders and a broader global economy. Watching the current crypto market patterns, we can expect an interesting paradox emerging soon – crypto startups with no real utility […]

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arXiv:2601.09852v1 Announce Type: new Abstract: Language places subtle constraints on how we make inductive inferences. Developmental evidence by Gelman et al. (2002) has shown children (4 years and older) to differentiate among generic statements (“Bears are daxable”), universally quantified NPs (“all bears are daxable”) and indefinite plural NPs (“some bears are daxable”) in extending novel properties to a specific member (all > generics > some), suggesting that they represent these types of propositions differently. We test if these […]

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arXiv:2604.01396v1 Announce Type: new Abstract: As AI becomes more common in students’ everyday experiences, a major challenge for K-12 AI education is designing learning experiences that can be meaningfully integrated into existing subject-area instruction. This paper presents the design and implementation of an AI4K12-aligned curriculum that embeds AI learning goals within a rural middle school science classroom using Breadth-First Search (BFS) as an accessible entry point to AI problem-solving. Through unplugged activities and an interactive simulation environment, students […]

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Self-supervised learning has emerged as a major technique for the task of learning from unlabeled data, where the current methods mostly revolve around alignment of representations and input recon struction. Although such approaches have demonstrated excellent performance in practice, their scope remains mostly confined to learning from observed data and does not provide much help in terms of a learning structure that is predictive of the data distribution. In this paper, we study some of the recent developments […]

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arXiv:2601.12023v1 Announce Type: new Abstract: Semi-implicit variational inference (SIVI) enhances the expressiveness of variational families through hierarchical semi-implicit distributions, but the intractability of their densities makes standard ELBO-based optimization biased. Recent score-matching approaches to SIVI (SIVI-SM) address this issue via a minimax formulation, at the expense of an additional lower-level optimization problem. In this paper, we propose kernel semi-implicit variational inference (KSIVI), a principled and tractable alternative that eliminates the lower-level optimization by leveraging kernel methods. We show […]

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arXiv:2602.09185v1 Announce Type: new Abstract: AI coding agents are rapidly transforming software engineering by performing tasks such as feature development, debugging, and testing. Despite their growing impact, the research community lacks a comprehensive dataset capturing how these agents are used in real-world projects. To address this gap, we introduce AIDev, a large-scale dataset focused on agent-authored pull requests (Agentic-PRs) in real-world GitHub repositories. AIDev aggregates 932,791 Agentic-PRs produced by five agents: OpenAI Codex, Devin, GitHub Copilot, Cursor, and […]

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Anthropic seems to be preparing to add Cowork support to Claude’s mobile apps, based on some reports. Bits of code and interface clues in the apps suggest they are working to bring their AI-powered workspace beyond the desktop, opening the experience to anyone using a phone or tablet. Anthropic has not made anything official yet, but these hints show where their product plans might go next. Anthropic rolled out Cowork to help users delegate tasks and collaborate with […]

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arXiv:2603.03308v1 Announce Type: new Abstract: How does the conversational past of large language models (LLMs) influence their future performance? Recent work suggests that LLMs are affected by their conversational history in unexpected ways. For instance, hallucinations in prior interactions may influence subsequent model responses. In this work, we introduce History-Echoes, a framework that investigates how conversational history biases subsequent generations. The framework explores this bias from two perspectives: probabilistically, we model conversations as Markov chains to quantify state […]

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