DeepCoT: Deep Continual Transformers for Real-Time Inference on Data Streams

The article introduces DeepCoT, a novel approach using continual transformers for real-time inference on data streams. The focus is on adapting transformers to handle continuously arriving data, which is a significant challenge in many applications. The use of 'continual' suggests a focus on learning and adapting over time, rather than retraining from scratch. The title clearly states the core contribution.

• •Focus on real-time inference.
• •Utilizes continual transformers.
• •Addresses the challenge of handling continuously arriving data.