arXiv:2602.06049v1 Announce Type: new Abstract: Slogans are concise and memorable catchphrases that play a crucial role in advertising by conveying brand identity and shaping public perception. However, advertising fatigue reduces the effectiveness of repeated slogans, creating a growing demand for novel, creative, and insightful slogan generation. While recent work leverages large language models (LLMs) for this task, existing approaches often produce stylistically redundant outputs that lack a clear brand persona and appear overtly machine-generated. We argue that effective […]

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A new paper by Avihu Mordechai Levy (StarkWare) describes Quantum-Safe Bitcoin (QSB), a way to spend legacy Bitcoin outputs that would stay secure even if an attacker had a cryptographically relevant quantum computer. It works inside today’s Bitcoin Script with no soft fork. Under the paper’s Shor-only threat model, its recommended configuration (Config A) achieves roughly 2^118 second-preimage resistance while fitting inside Bitcoin’s existing legacy script limits of 201 opcodes and under 10,000 bytes (§4.5, §2.2). The spender […]

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RAG is everywhere—and that’s not surprising. It’s one of the most practical ways to make large document collections queryable without building brittle, domain-specific parsers for every question type. The catch is that what works in a controlled demo often degrades quickly when you put it in front of real enterprise PDFs: scanned contracts, compliance filings, medical records, policies, and the long tail of layout and quality issues that come with them. In production, the “RAG problem” is less […]

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This is Part 4 of a 4-part series on the CAP Theorem and distributed systems trade-offs. Read Part 1, Part 2, or Part 3 if you haven’t already. We’ve dedicated three posts to treating CP and AP as binary choices. etcd is CP. DynamoDB is AP. Pick a side. But that’s not how real systems work. MongoDB can be CP or AP depending on your configuration. Cassandra lets you choose per query. Even PostgreSQL, which we covered as […]

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arXiv:2602.20306v1 Announce Type: new Abstract: High-fidelity computational models of cardiac mechanics provide mechanistic insight into the heart function but are computationally prohibitive for routine clinical use. Surrogate models can accelerate simulations, but generalization across diverse anatomies is challenging, particularly in data-scarce settings. We propose a two-step framework that decouples geometric representation from learning the physics response, to enable shape-informed surrogate modeling under data-scarce conditions. First, a shape model learns a compact latent representation of left ventricular geometries. The […]

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arXiv:2601.16447v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated exceptional performance in reasoning tasks such as mathematics and coding, matching or surpassing human capabilities. However, these impressive reasoning abilities face significant challenges in specialized domains. Taking Go as an example, although AlphaGo has established the high performance ceiling of AI systems in Go, mainstream LLMs still struggle to reach even beginner-level proficiency, let alone perform natural language reasoning. This performance gap between general-purpose LLMs and domain […]

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The life of a prescription at Amazon Pharmacy From pricing estimation and regulatory compliance to inventory management and chatbot assistants, machine learning models help Amazon Pharmacy customers stay healthy and save time and money. Conversational AI Alexandre Alves Anita Vila September 30, 01:32 PM October 02, 11:42 AM Pharmacies play a vital role in ensuring patients health, but the process of dispensing medications is far more complex than it may appear. At Amazon Pharmacy, we are using artificial […]

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arXiv:2603.25889v1 Announce Type: new Abstract: Head-mounted devices integrated with eye tracking promise a solution for natural human-computer interaction. However, they typically require per-user calibration for optimal performance due to inter-person variability. A differential personalization approach using Siamese architectures learns relative gaze displacements and reconstructs absolute gaze from a small set of calibration frames. In this paper, we benchmark Siamese personalization on polarization-enabled eye tracking. For benchmarking, we use a 338-subject dataset captured with a polarization-sensitive camera and 850 […]

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arXiv:2604.07420v1 Announce Type: new Abstract: Kuaishou serves over 400 million daily active users, processing hundreds of millions of search queries daily against a repository of tens of billions of short videos. As the final decision layer, the reranking stage determines user experience by optimizing whole-page utility. While traditional score-and-sort methods fail to capture combinatorial dependencies, Generative Reranking offers a superior paradigm by directly modeling the permutation probability. However, deploying Generative Reranking in such a high-stakes environment faces a […]

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