Sports Understanding
4 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Sports Understanding
DeepSportRadar-v1
Most implemented papers
DeepSportradar-v1: Computer Vision Dataset for Sports Understanding with High Quality Annotations
deepsportradar/player-reidentification-challenge
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With the recent development of Deep Learning applied to Computer Vision, sport video understanding has gained a lot of attention, providing much richer information for both sport consumers and leagues.
Scaling Language Models: Methods, Analysis & Insights from Training Gopher
Language modelling provides a step towards intelligent communication systems by harnessing large repositories of written human knowledge to better predict and understand the world.
Training Compute-Optimal Large Language Models
We investigate the optimal model size and number of tokens for training a transformer language model under a given compute budget.
Learning to Perform Complex Tasks through Compositional Fine-Tuning of Language Models
In this work, we present compositional fine-tuning (CFT): an approach based on explicitly decomposing a target task into component tasks, and then fine-tuning smaller LMs on a curriculum of such component tasks.
