arXiv:2602.17633v1 Announce Type: cross Abstract: Reasoning with LLMs increasingly unfolds inside a broader verification loop. Internally, systems use cheap checks, such as self-consistency or proxy rewards, which we call weak verification. Externally, users inspect outputs and steer the model through feedback until results are trustworthy, which we call strong verification. These signals differ sharply in cost and reliability: strong verification can establish trust but is resource-intensive, while weak verification is fast and scalable but noisy and imperfect. We […]

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arXiv:2601.07968v1 Announce Type: new Abstract: We study the theoretical problem of synthesizing multiple DNA strands under spatial constraints, motivated by large-scale DNA synthesis technologies. In this setting, strands are arranged in an array and synthesized according to a fixed global synthesis sequence, with the restriction that at most one strand per row may be synthesized in any synthesis cycle. We focus on the basic case of two strands in a single row and analyze the expected completion time […]

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Python operators enable you to perform computations by combining objects and operators into expressions. Understanding Python operators is essential for manipulating data effectively. This video course covers arithmetic, comparison, Boolean, identity, membership, bitwise, concatenation, and repetition operators, along with augmented assignment operators. You’ll also learn how to build expressions using these operators and explore operator precedence to understand the order of operations in complex expressions. By the end of this video course, you’ll understand that: Arithmetic operators perform […]

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arXiv:2602.15037v1 Announce Type: new Abstract: As large language models (LLMs) advance toward expert-level performance in engineering domains, reliable reasoning under user-specified constraints becomes critical. In circuit analysis, for example, a numerically correct solution is insufficient if it violates established methodological conventions such as mesh directionality or polarity assignments, errors that can propagate in safety-critical systems. Yet it remains unclear whether frontier models truly apply first-principles reasoning or rely on entrenched training priors that conflict with explicit instructions. We […]

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arXiv:2602.13200v1 Announce Type: new Abstract: The purpose of this paper is to model traffic in Ad Hoc network of Unmanned Aerial Vehicles and demonstrate a way for adapting communication channel using Artificial Intelligence. The modeling was based on the original model of Ad Hoc network including 20 Unmanned Aerial Vehicles. The dependences of packet loss on the packet size for different transmission powers, on the packet size for different frequencies, on Unmanned Aerial Vehicles flight area and on […]

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arXiv:2602.12351v1 Announce Type: new Abstract: This paper develops LongNav-R1, an end-to-end multi-turn reinforcement learning (RL) framework designed to optimize Visual-Language-Action (VLA) models for long-horizon navigation. Unlike existing single-turn paradigm, LongNav-R1 reformulates the navigation decision process as a continuous multi-turn conversation between the VLA policy and the embodied environment. This multi-turn RL framework offers two distinct advantages: i) it enables the agent to reason about the causal effects of historical interactions and sequential future outcomes; and ii) it allows […]

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arXiv:2602.04364v1 Announce Type: new Abstract: Prediction sets provide a means of quantifying the uncertainty in predictive tasks. Using held out calibration data, conformal prediction and risk control can produce prediction sets that exhibit statistically valid error control in a computationally efficient manner. However, in the standard formulations, the error is only controlled on average over many possible calibration datasets of fixed size. In this paper, we extend the control to remain valid with high probability over a cumulatively […]

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Get-Star is a fully client-side, browser-based meta-search tool that runs parallel queries across 42 sites, prioritizes user privacy, and earned a 27 Proof of Usefulness score for real-world utility.

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The chart looked convincing. A clear, upward slope, a quick shift right after a new feature rollout, and a healthy percentage increase in bold. Heads nodded in the meeting room. There was a remark: “This clearly worked.” Then the discomforting follow-up: “But how do we know this happened because of the feature?” That question too often asked too late, or not at all — is where econometric statistics intervenes, quietly, to affect the outcome of real-world decisions. The […]

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