Memory Bear AI Memory Science Engine for Multimodal Affective Intelligence: A Technical Report

ArXi:2603.22306v1 Announce Type: new Affective judgment in real interaction is rarely a purely local prediction problem. Emotional meaning often depends on prior trajectory, accumulated context, and multimodal evidence that may be weak, noisy, or incomplete at the current moment. Although multimodal emotion recognition (MER) has improved the integration of text, speech, and visual signals, many existing systems remain optimized for short-range inference and provide limited for persistent affective memory, long-horizon dependency modeling, and robust interpretation under imperfect input.