Token Sequence

Token sequences, ordered sets of discrete units representing text or other data, are central to many large language model (LLM) applications. Current research focuses on optimizing token sequence handling for improved efficiency, security, and performance, exploring techniques like speculative decoding, variable-length training curricula, and novel tokenization methods (e.g., wavelet-based). These advancements aim to address challenges such as computational cost, vulnerability to adversarial attacks, and the efficient processing of long sequences, ultimately impacting the speed, accuracy, and safety of LLMs across diverse applications.