Better Representation

"Better representation" in machine learning focuses on developing more effective and efficient ways to encode data, improving the performance of downstream tasks. Current research emphasizes enhancing representations through various techniques, including novel tokenizer designs for language models, function-space embeddings for knowledge graphs, and the use of contrastive learning and self-supervised methods across diverse modalities (images, videos, text). These advancements are crucial for improving the accuracy, robustness, and efficiency of machine learning models in various applications, from autonomous driving to medical image analysis and recommender systems.