On What We Can Learn from Low-Resolution Data

ArXi:2605.12168v1 Announce Type: new Artificial intelligence systems typically rely on large, centrally collected datasets, a premise that does not hold in many real-world domains such as healthcare and public institutions. In these settings, data sharing is often constrained by storage, privacy, or resource limitations. For example, small wearable devices may lack the bandwidth or energy capacity needed to and transmit high-resolution data, leading to aggregation during data collection and thus a loss of information.