Актуализира се ежедневно1524 проверени истории
Проверено от източници AI покритие на пускането на продукти, промените в политиките, изследванията на безопасността и индустриалните ходове, обяснено на ясен език от образователен екип на неправителствена организация.
Всяка история се свързва с най-силните налични доказателства: оригинални източници, когато са налични, иначе ясно приписани доклади.
Какво се случи, защо има значение и какво да гледате – без данък върху жаргона.
Когато сигналът е слаб, ние не публикуваме нищо, вместо да допълваме емисията.
Нарастващ поток от проверени гледни точки за хора, които трябва да разберат AI, без да преследват реклами.
A new preprint reports that several normalized metrics used to compare language models across languages can introduce biases linked to tokenization, encoding and orthographic differences. It argues that sentence-level negative log-likelihood over semantically equivalent sequences produces more consistent comparisons.
A new dataset evaluates large language models as diagnostic agents in interactive clinical encounters rather than through isolated questions. MTDiag combines cases from emergency medicine, clinical records and published case reports, and proposes knowledge-grounded metrics beyond diagnostic accuracy.
Researchers created HealthBench-Psych, a 610-conversation mental-health subset of OpenAI’s HealthBench, and released its evaluation pipeline, model responses, grades and analysis code.
A survey accepted to Findings of EMNLP 2026 catalogs 80 methods for adapting foundation models without human labels, preference data, stronger teachers or executable verifiers. It warns that internal learning signals can either improve a model or recursively amplify its errors.
A new preprint reports that language models encode dialectal English unequally during tokenization, pre-training, post-training and inference, even when paired texts have the same meaning.
A new preprint proposes triggering bias corrections only when evidence of stereotyping accumulates during an LLM’s reasoning, reporting fewer interventions than fixed-interval methods but important accuracy tradeoffs across model types.
A paper accepted to Findings of EMNLP 2026 introduces OmniPhys, a benchmark of 15,246 physics questions and 19,850 images drawn from Chinese educational corpora. It evaluates multimodal AI systems on both physics reasoning and the generation of structured physics diagrams.
A new arXiv preprint introduces DCGC, a masked-diffusion framework that uses an upstream draft to revise reasoning globally instead of allowing early mistakes to propagate.
A new arXiv paper introduces VietAIDetector, an open-source zero-shot tool designed to identify AI-generated Vietnamese text without domain-specific training data. The authors say it supports long and scanned documents and outperforms methods developed primarily for English on out-of-domain evaluations.
An arXiv preprint introduces ReliableRAG, a retrieval-augmented generation framework that scores individual evidence triples for relevance and credibility before constructing multi-step answers.
A new arXiv paper introduces TOPAS, a scheduler that jointly manages cached LLM prefixes and request execution in multi-stage agent workflows. The authors report lower job-completion times than their tested baselines on synthetic workflows and two MetaGPT software-development workloads.
A new arXiv paper describes EmoVec, an inference-time method that injects emotion-specific vectors into language models to adjust emotional intensity while preserving the response’s meaning, fluency and coherence, according to experiments reported by the authors.
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