Findings suggest that, in the absence of external authorship labels, listeners spontaneously form judgments about the creative agent of music that are stably associated with aesthetic evaluation and may constitute an endogenous perceptual bias in the reception of AI-generated music.
Junfang Chang, Yue-Qi Jing· Frontiers in Psychology· 0 citations
The theology chapters may be the most valuable in the book for a broad audience that spans pastors, church leaders, and lay people who may or may not regularly work with AI, and will help those teaching and preaching to connect doctrine to current and emerging AI content and methodology.
Seán A. O'Callaghan, Paul Hoffman· Perspectives on Science and...· 0 citations
It is demonstrated that lemmatization does not produce uniform gains across architectures: while linear models and croBERT display small but measurable improvements from morphological normalization, non-linear models such as RBF SVM and neural networks experience substantial declines in performance.
I. Ljubi, M. Horvat, G. Gledec et al.· Electronics· 0 citations
Results showed that long-context LLMs tended to achieve higher accuracy than smaller models, suggesting that LLMs are currently better suited to support human-in-the-loop root cause analysis than to fully automate it, and motivating further work to improve prediction accuracy for log-based RCA.
Rahmanu Hermawan, Alessio Bucaioni, Eduard Paul Enoiu et al.· Innovations in Systems and S...· 0 citations
Reach audiences
Advertise in front of researchers, engineers, and readers.
This work introduces CytoGate-Bench, a benchmark that reformulates this per-step procedure as a zero-shot, panel-agnostic task for large language models, and contributes a public benchmark that tests precisely that ability across 11 human cohorts.
Jaesik Kim, Byounghan Lee, N. Ahn et al.· bioRxiv· 0 citations
This work demonstrates that MGTP-Seg not only provides an accurate, interpretable, and clinically relevant solution for automatic GTV delineation, but also offers a novel methodological framework to fuse spatial priors with semantic knowledge in medical image analysis.
Cheng-Wei Chen, Hong-Fei Sun, Yuxuan Yao et al.· Physics in Medicine and Biol...· 0 citations
BACKGROUND
Underreporting is a defining problem in the registration of workplace violence across public services. This is reinforced by inconsistent, often poor incident descriptions and the absence of a clear, shared nomenclature. Without an ontology-backed structure, similar events are recorded differently across set...
I. Steenhout, Ronald Buyl· JMIR Research Protocols· 0 citations
This work extends the classical Schelling segregation model with a hybrid population: ordinary agents classify neighbors using the standard symbolic rule, while one agent delegates this task to an LLM through tool calls, providing a minimal but controlled setting where the semantic, operational, and computational behav...
Stefano Blando, Emanuele Guerrazzi, R. Porcedda et al.· arXiv.org· 1 citation
NavAI is an extensible navigation framework that leverages large language models (LLMs) to support both basic action commands and multi-step goal-oriented navigation through an application-agnostic screenshot-and-control interface and explores optimization strategies for virtual scene understanding and navigation goal...
Jiajie Wang, Sumesh Surendran Letha, M. DiGiovanni et al.· International Conference on...· 0 citations
Experiments show that FiUni can effectively infer latent batch-level task affiliations and achieve competitive performance against advanced task-aware CL methods with fewer trainable parameters.
Dezheng Han, Anlan Zhang, Zhiwu Zhu et al.· 0 citations
Experiments across video understanding and reasoning benchmarks show that the Evidence-Grounded Self-Teacher framework consistently improves upon Standard OPSD across multiple backbones and achieves performance comparable to GRPO while requiring substantially less training time, establishing an effective and efficient...
Zi-Yue Wang, Shi-Qi Huang, Wei-Wen Xu et al.· 5 citations
This work proposes a composite metric that combines two orthogonal criteria: information retention and throughput gains and finds that it allocates more resources to the most expressive layers compared to evolutionary search, specialized accelerators, or Shapley-value-based approaches that require expensive approximate...
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
Flint-interactive gives AI agents a language for creating interactive visualizations. Click a chart, filter data, highlight related content, and explore beyond the view the author originally chose. The post Flint-interactive: A language for creating interactive data visualizations appeared first on Microsoft Research.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
