Variance Reduction
A statistical technique aimed at reducing the variability of an estimator to improve the reliability of the results.
Category: General AI/ML
Shortcut Heuristics
Simplified reasoning strategies that models use to achieve results without fully understanding the underlying spatial relationships.
Predictive Sensing Inference
Inference strategies tailored to improve model performance on specific benchmarks by predicting sensory information.
NoSense
A baseline model that discards temporal structure and utilizes a bag-of-words approach with SigLIP for video analysis.
SigLIP
A model that uses a bag-of-words approach for processing video data, focusing on significant visual features.
VSI-Super-Counting
A benchmark that assesses the ability of models to count unique objects in video sequences.
VSI-Super-Recall
A benchmark designed to evaluate the performance of models in recalling spatial information from video data.
Sparsity-Aware Retraining
A retraining process that takes into account the sparsity of the model, focusing on recovering performance without reactivating pruned connections.
One-Shot Pruning
A pruning strategy that eliminates weights in a single pass rather than through iterative cycles of training and pruning.
Importance Score Estimation
A technique used to evaluate the significance of each parameter in a model to determine which ones can be pruned without significantly affecting performance.