VideoFDB is a new benchmark and LM-as-judge framework for evaluating full-duplex audio-visual-to-audio-visual conversational agents on nonverbal dynamics from real video calls.
Canonical reference
The stability-plasticity dilemma: investigating the continuum from catastrophic forgetting to age-limited learning effects.Fron- tiers in Psychology, V olume 4 - 2013, 2013
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DARE-EEG is a self-supervised EEG foundation model that enforces mask-invariance via contrastive mask alignment and momentum anchor alignment, plus conv-linear-probing for heterogeneous setups, achieving SOTA accuracy and cross-dataset portability.
Developers using AI showed the same core problem-solving behaviors as those without but differed in how they became stuck and recovered, with AI helping or hindering in specific cases.
AI-authored goals produce higher SMART quality scores but lower psychological ownership, commitment, importance, and goal-directed behavior than self-authored goals, with ownership as the mediating mechanism.
Eye contact norms create three recurring access barriers for visually impaired people in mixed-ability groups, reframing accessible design as support for explicit interaction contracts instead of gaze visibility.
Information defined as maximum-caliber deviation derives IIT 3.0 cause-effect repertoires from constrained entropy maximization and equates to prediction error under CLT and LDT.
People reject cookie + $2 offers from robots more than cookie alone due to inferred phantom costs, accepting more from robots than humans overall with no embodiment effect for robots.
Exploratory experience produces more spatially organized and transition-preserving predictive representations in maze navigation for both agents and mice.
Self-generated replay from language models nearly eliminates catastrophic forgetting during finetuning except when models are pretrained close to saturation.
Online posts by early childhood educators focus more on workplace demands than resources, with fear as the leading emotion and higher sadness and anger in demand-related posts.
Active inference model unifies human collision avoidance by reproducing meta-analysis aggregates and simulator-specific effects on response timing, maneuver selection, and execution.
A literature survey that categorizes high-level abstract concept image classification tasks in CV into semantic clusters and identifies persistent challenges and opportunities for hybrid AI approaches.
Response-time propensities estimated from tutoring logs are stable within students and predict learning efficiency conditionally on proficiency and practice stage.
LLMs accelerate research workflows from idea generation to writing but introduce challenges like hallucination, bias, opacity, and ten systemic risks requiring new governance frameworks.
Exploratory study reports measurable differences in emotion and immersion from systematic changes to frequency, dynamics, and directionality in film audio mixes.
The work introduces a visualization framework that turns imperceptible micro-expressions into perceptible cues and outlines a planned pilot study to test effects on empathic experience.
A review of 22 studies identifies five clusters of factors affecting autonomy and agency in HRI while noting limited and fragmented evidence.
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DARE-EEG: A Foundation Model for Mining Dual-Aligned Representation of EEG
DARE-EEG is a self-supervised EEG foundation model that enforces mask-invariance via contrastive mask alignment and momentum anchor alignment, plus conv-linear-probing for heterogeneous setups, achieving SOTA accuracy and cross-dataset portability.