Challenges and Applications of Large Language Models
This provides a foundational resource for machine learning researchers to navigate the rapidly evolving LLM landscape, though it is incremental as it synthesizes existing knowledge rather than introducing new methods.
The paper tackles the challenge of identifying remaining problems and successful applications in the fast-paced field of Large Language Models (LLMs), aiming to establish a systematic overview to help researchers understand the current state and become productive.
Large Language Models (LLMs) went from non-existent to ubiquitous in the machine learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify the remaining challenges and already fruitful application areas. In this paper, we aim to establish a systematic set of open problems and application successes so that ML researchers can comprehend the field's current state more quickly and become productive.