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Found 6 papers, 2 papers with code
Enabling High-Sparsity Foundational Llama Models with Efficient Pretraining and Deployment
We achieve this for the LLaMA-2 7B model by combining the SparseGPT one-shot pruning method and sparse pretraining of those models on a subset of the SlimPajama dataset mixed with a Python subset of The Stack dataset.
Lidar Panoptic Segmentation and Tracking without Bells and Whistles
Our network is modular by design and optimized for all aspects of both the panoptic segmentation and tracking task.
Completely Self-Supervised Crowd Counting via Distribution Matching
Dense crowd counting is a challenging task that demands millions of head annotations for training models.
Unsupervised Domain Adaptation for Learning Eye Gaze from a Million Synthetic Images: An Adversarial Approach
Such domain difference deteriorates test time performances of models trained on synthetic examples.
Representation-Aggregation Networks for Segmentation of Multi-Gigapixel Histology Images
Convolutional Neural Network (CNN) models have become the state-of-the-art for most computer vision tasks with natural images.
Recurrent Memory Addressing for describing videos
In this paper, we introduce Key-Value Memory Networks to a multimodal setting and a novel key-addressing mechanism to deal with sequence-to-sequence models.
