Challenges and Applications of Large Language Models

Published on Jul 19
· Featured in Daily Papers on Jul 20


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.



Interesting paper and easy to capture key insights from the colored boxes. I have one question about the first challenge about dataset, the "2.1 Unfathomable Datasets" and the challenges related to evaluating dataset quality. I was particularly interested in the possible presence of copyrighted content or Personally Identifiable Information (PII) in the training dataset, which could potentially lead to legal issues for a flagship LLM project.

I'm curious to know if the authors or other readers are aware of any existing cases where such challenges with datasets have indeed resulted in serious legal consequences for a large language model project. It would be valuable to understand how the community is addressing or mitigating these legal risks while pushing the boundaries of LLM research and applications.

Any insights or examples related to this topic would be greatly appreciated. Thank you!

Sign up or log in to comment

Models citing this paper 0

No model linking this paper

Cite in a model to link it from this page.

Datasets citing this paper 0

No dataset linking this paper

Cite in a dataset to link it from this page.

Spaces citing this paper 0

No Space linking this paper

Cite in a Space to link it from this page.

Collections including this paper 1