Tag
A user shares concerns about reward hacking patterns in the MiMo dataset, advising caution when using it for training AI models.
This paper presents data stories as narrative documents combining explanatory text, images, and executable SPARQL queries to enhance accessibility and quality assessment in cultural heritage knowledge graphs, using an AI-supported authoring platform called LODEON.
This paper introduces XAI-Arena, an LLM-as-a-judge framework for scalable and reproducible evaluation of explainable AI explanation quality, showing strong correlation with human judgments.
fmetrics is an open-source library in C and Zig for computing fast perceptual image and video fidelity metrics such as IW-SSIM, MS-SSIM, SSIMULACRA2, Butteraugli, and CVVDP, with validated correlation to human ratings.
This paper proposes a model-based approach to assess massively multilingual parallel data by decomposing it into parallelism assessment and reference-free quality estimation, finding that no single universal metric works across all language directions.
This paper introduces a knowledge-based approach using knowledge graph embeddings to automatically assess big data quality by predicting missing edges between context representations and quality rules, outperforming traditional matching methods.