Intent Lenses infer capture-time user intent from photos via LLMs to create dynamic, reusable interactive objects that generate and organize structured visual notes for later sensemaking.
A review on multi-label learning algorithms
3 Pith papers cite this work. Polarity classification is still indexing.
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Physics-informed graph attention networks predict multi-phase equilibria in Ag-Bi-Cu-Sn alloys with 96% exact-set accuracy on in-domain data and strong generalization to unseen sections.
Bielik Guard delivers compact Polish safety classifiers with F1 scores near 0.79 and superior real-prompt precision over baselines.
citing papers explorer
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Intent Lenses: Inferring Capture-Time Intent to Transform Opportunistic Photo Captures into Structured Visual Notes
Intent Lenses infer capture-time user intent from photos via LLMs to create dynamic, reusable interactive objects that generate and organize structured visual notes for later sensemaking.
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Multi-Label Phase Diagram Prediction in Complex Alloys via Physics-Informed Graph Attention Networks
Physics-informed graph attention networks predict multi-phase equilibria in Ag-Bi-Cu-Sn alloys with 96% exact-set accuracy on in-domain data and strong generalization to unseen sections.
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Bielik Guard: Efficient Polish Language Safety Classifiers for LLM Content Moderation
Bielik Guard delivers compact Polish safety classifiers with F1 scores near 0.79 and superior real-prompt precision over baselines.