Length Constraint

Length constraint in various machine learning applications, particularly large language models (LLMs), is a significant research area focused on improving efficiency and performance while maintaining accuracy. Current efforts concentrate on developing model-agnostic methods to control generated text length, desensitizing optimization algorithms to length biases, and optimizing prediction set sizes in conformal prediction. These advancements aim to address issues like excessive verbosity in LLMs, improve the efficiency of LLM-based systems for tasks such as click-through rate prediction, and enhance the overall usability and resource efficiency of AI systems.