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arXiv:2605.28825v1 Announce Type: new Abstract: Large language models (LLMs) frequently encode factual and reasoning knowledge in their internal representations that is not faithfully reflected in their surface-level outputs — a phenomenon known as emph{latent knowledge}. Existing approaches to eliciting latent knowledge, such as Contrastive Consistency Search (CCS), rely on contrastive activation patterns and struggle with complex multi-step reasoning tasks, while mechanistic interpretability tools have primarily been used to emph{understand} model behavior rather than to emph{extract} hidden knowledge. We […]

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arXiv:2605.28824v1 Announce Type: new Abstract: Constructing artificial lexicons that are pronounceable, typologically plausible, and semantically structured remains an open challenge in computational linguistics. Existing conlang generators either lack formal phonotactic guarantees or delegate generation to opaque, non-reproducible LLM-based pipelines. We propose a modular framework that samples phoneme inventories from PHOIBLE, generates word forms under interchangeable phonological grammars (deterministic, OT, and MaxEnt), and assigns meanings via a Swadesh–Leipzig–Jakarta ontology with explicit form–meaning alignment. Evaluation on character $n$-gram perplexity, log-likelihood, […]

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arXiv:2605.28823v1 Announce Type: new Abstract: As the influence of LLMs expands, it is imperative to gain insight into their decisions. One way to do that is to develop probes that detect the presence or absence of a broad set of concepts within the embeddings computed in an LLM – which is what we might say a model is “thinking” about. Such probes should be low-cost and easily applicable to any LLM, so that monitoring for many concepts is […]

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arXiv:2605.28822v1 Announce Type: new Abstract: Defect grading of power transmission equipment (DGPTE) is crucial to the stability of electric energy transmission. Although existing machine learning methods exhibit strong capabilities in defect detection, they are plagued by difficulties in integrating expert experience and facing class imbalance in more refined defect grading field. To address this issue, this paper introduces a novel defect grading framework based on multimodal large language model (MLLM). Specifically, this approach maximizes the commercial MLLMs’ potential […]

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OpenAI launches Rosalind Biodefense, expanding trusted access to GPT-Rosalind for vetted developers and U.S. government partners advancing biodefense, public health, and pandemic preparedness through frontier AI.

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Maybe you already know what AI is. But then your manager, a friend, or your mom asks you to explain it, and suddenly it becomes harder than expected. This article is my attempt to explain AI in plain words — the way I would explain it to someone who does not care about tokens, weights, gradients, or architecture diagrams. So, let me try. We want to speed up our businesses with AI. We trust it to help with […]

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Let’s learn about Founder Stories via these 308 free blog posts. They are ordered by HackerNoon reader engagement data. Visit the Learn Repo or LearnRepo.com to find the most read blog posts about any technology. Founders, very often, solve problems that we don’t know we have yet. 1. Building a Gaming Metaverse on 750 Acres of Land in Costa Rica Alóki is based on an intricate relationship with the 750 acres of jungle in Costa Rica. 2. The […]

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OpenAI shares guidance on third-party AI evaluations, covering how to assess model capabilities, safeguards, and validity for frontier systems.

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