Actualizado diariamente1513 historias verificadas
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Linuxiac reports that Shadowfetch Linux 3.0 introduces Fireline, a set of sandboxing, checkpoint, audit and controlled-tool features for autonomous coding agents. The source does not independently verify the system’s security or performance claims.
A new arXiv preprint proposes an AI-based method for measuring how strongly job titles and skills are associated with digital work. Applied to millions of Dutch job profiles, the method identifies uneven digitalization and pathway-dependent movement toward digital occupations.
An arXiv preprint reports that five large language models changed harmful-content classifications across Urdu scripts and English translations, revealing a measurable “Missed-in-Urdu” safety gap.
A four-month deployment study found that an AI system's ability to recall past facts did not predict user satisfaction or whether it naturally used those facts in conversation.
A new benchmark reports that eight large language models frequently fail to detect conflicting evidence or preserve correct analyses when spreadsheets and tables are altered.
A new arXiv preprint reports that automated metrics and LLM judges often fail to match human assessments of creativity in short stories, with judges systematically favoring AI-generated writing styles.
An arXiv preprint reports that representation, structural screening and ranking choices can substantially alter which AI-generated Big Five items reach psychometrician review, even when global summaries appear stable.
A preprint reports that four multilingual eighth-grade students challenged LLM classifications of their math discussions, arguing that adult annotations and standard scores can miss students’ own interpretations.
A new arXiv study reports that giving language models access to stored examples improves their sensitivity to syntactic contrasts involving rare words, although the gap is not eliminated.
An arXiv study proposes a two-layer detector for package-name hallucinations in local coding language models, reporting that hallucination rates rose from 0–10% on routine prompts to 40–73% on adversarial slopsquatting prompts.
A new arXiv paper introduces AgentSpec, a speculative-decoding method designed to reduce response-time degradation when LLM agents run in large batches. The authors evaluate it across five workloads and four models from four LLM families in vLLM.
A new arXiv preprint proposes measuring the geometry of model inference to identify deceptive behavior that conventional linear probes may miss.
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