arXiv:2605. 16972v2 Announce Type: replace-cross Abstract: Cultural heritage exhibitions often struggle to sustain attention and support reflective engagement.
Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.
The Living Library is an end‑to‑end framework that converts fragmented digital archives into governed, conversational exhibit experiences. Developed at the Theodore Roosevelt Presidential Library, it digitizes a 300,000‑record collection, enriches it with OCR and metadata, and publishes it to a hybrid dense/semantic index. The system supports curator review via the Archivist App, powers a researcher interface, and runs Talk to TR—a museum exhibit where a digital human embodiment of Theodore Roosevelt answers visitors’ questions using Cross‑Era Analogical Grounding and dual‑path retrieval to keep responses grounded and responsive.
arXiv:2606. 09846v1 Announce Type: cross Abstract: Visual art remains largely inaccessible to blind and low-vision (BLV) audiences due to brief or absent alt-text, which rarely conveys the sensory, spatial, or emotional qualities of an artwork.
Vision-language models (VLMs) have made interactive digital museums increasingly feasible by connecting 3D digitization with natural-language artifact exploration. However, in cultural heritage domains such as ancient Greek pottery, reliable VLM assistance is limited by two challenges.
arXiv:2607. 03731v1 Announce Type: cross Abstract: Creating 3D assets for virtual reality requires modeling expertise, which restricts the authorship of immersive experiences.
arXiv:2606. 30026v1 Announce Type: cross Abstract: Audiovisual arts encompass diverse creative disciplines, including cinema, visual arts, stage performance, and game design, where artistic meaning arises from deliberate combinations of visual, auditory, and narrative elements (e.
MUSE is a new benchmark designed to evaluate large vision‑language models on artistic image understanding within situated educational contexts. It separates image annotation from question generation, offering twelve tasks that cover visual perception, semantic and affective interpretation, cultural understanding, and compositional reasoning across diverse artistic images from Singaporean, Southeast Asian, and Western traditions. The benchmark reveals significant gaps in model performance, especially in affective interpretation and compositional reasoning, and highlights common failure modes for trustworthy educational multimodal systems.