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Multi-source AI news clustered, deduplicated, and scored 0–100 across authority, cluster strength, headline signal, and time decay.

  1. RESEARCH · Mastodon — fosstodon.org English(EN) · · [4 sources]

    If #AI concentrates scientific attention, might it also concentrate scientific blind spots? My new Zenodo preprint explores the hypothesis that shared AI search

    A new preprint by Bernd von Mallinckrodt hypothesizes that the concentration of scientific attention on AI might also lead to concentrated blind spots. The research explores how shared AI search infrastructures could influence not only what researchers discover but also what they collectively miss. AI

    IMPACT Suggests AI's focus could inadvertently narrow the scope of scientific inquiry.

  2. RESEARCH · Hugging Face Daily Papers English(EN) · · [3 sources]

    The Ghost Couple: Correlated LLM Name Priors and Their Haunting of the Web and Academic Publishing

    A new research paper reveals that large language models generate correlated "ghost" personas, such as Elena Vasquez and Marcus Chen, who appear across numerous AI-generated documents as experts or co-authors. These correlated name priors are specific to model families and versions, leaving detectable fingerprints. The study found these ghost authors have been used to create over 1,600 fake academic records on repositories like Zenodo, with fabricated publication dates, and have also formed synthetic research groups on platforms like ResearchGate. AI

    IMPACT Reveals LLM-generated personas are used to create fake academic records, impacting scholarly integrity and trust in AI-generated content.

  3. TOOL · arXiv cs.CL English(EN) · · [2 sources]

    A cross-domain tropical species dataset with Chinese vernacular names and CITES source links

    Researchers have developed a comprehensive dataset of over 410,000 tropical species, integrating taxonomic identifiers from multiple biodiversity databases. This dataset includes novel layers for trade and husbandry contexts, a Chinese vernacular name layer with provenance tracking, and links to CITES entries. The goal is to provide a structured resource for understanding and regulating tropical species across various domains, with a high percentage of species now having associated Chinese names. AI

  4. RESEARCH · arXiv cs.LG English(EN) · · [2 sources]

    HARMES: A Multi-Modal Dataset for Wearable Human Activity Recognition with Motion, Environmental Sensing and Sound

    Researchers have introduced HARMES, a new multi-modal dataset for wearable human activity recognition. The dataset combines motion sensing, environmental data, and audio from wrist-worn devices, totaling over 80 hours of data from 20 participants performing household activities. HARMES is designed to improve the recognition of daily living activities, which can be ambiguous with single modalities, and is significantly larger than previous datasets of its kind. AI

    HARMES: A Multi-Modal Dataset for Wearable Human Activity Recognition with Motion, Environmental Sensing and Sound

    IMPACT Provides a large, multi-modal dataset to advance research in wearable human activity recognition.

  5. RESEARCH · arXiv cs.CV English(EN) ·

    PhotIQA: A photoacoustic image data set with image quality ratings

    Researchers have introduced PhotIQA, a new dataset containing 1134 photoacoustic images rated by five experts on five quality properties. This dataset aims to address the lack of quality-rated medical images, which hinders the development and testing of image quality assessment algorithms, particularly for photoacoustic imaging. The publicly available dataset is intended to support the creation of more accurate IQA measures for medical imaging applications beyond photoacoustic imaging. AI

    PhotIQA: A photoacoustic image data set with image quality ratings

    IMPACT Provides a new benchmark dataset for evaluating AI-based image quality assessment algorithms in medical imaging.

  6. RESEARCH · Mastodon — fosstodon.org Deutsch(DE) ·

    Art History Loves Wiki 2026 Conference # ALW2026 new publication: von dem Bussche, Ruth: From the Inventory Card to the Master Database: A Probabilistic Procedure

    A new publication titled "Von der Inventarkarte zur Normdatenbank" by Ruth von dem Bussche has been presented at the Art History Loves Wiki 2026 Conference. The work details a probabilistic method for the automated indexing of historical artist names, utilizing a norm database approach. Conference slides for this presentation are available on Zenodo. AI

    Art History Loves Wiki 2026 Conference # ALW2026 new publication: von dem Bussche, Ruth: From the Inventory Card to the Master Database: A Probabilistic Procedure

    IMPACT Presents a novel method for automated indexing of historical artist names, potentially improving digital humanities research tools.