Monday 2024-06-24 Assorted Links
Assorted Links links
Published: 2024-06-24
Monday 2024-06-24 Assorted Links

Assorted links for Monday, June 24:

  1. The time smart quotes prevented the entire Office division from committing code
  2. Video annotator: a framework for efficiently building video classifiers using vision-language models and active learning

    We introduce a novel framework, Video Annotator (VA), which leverages active learning techniques and zero-shot capabilities of large vision-language models to guide users to focus their efforts on progressively harder examples, enhancing the model’s sample efficiency and keeping costs low.

    VA seamlessly integrates model building into the data annotation process, facilitating user validation of the model before deployment, therefore helping with building trust and fostering a sense of ownership. VA also supports a continuous annotation process, allowing users to rapidly deploy models, monitor their quality in production, and swiftly fix any edge cases by annotating a few more examples and deploying a new model version.

  3. PVF: A novel metric for understanding AI systems’ vulnerability against SDCs in model parameters

    Parameter vulnerability factor (PVF) is a novel metric we’ve introduced with the aim to standardize the quantification of AI model vulnerability against parameter corruptions.

  4. Keeping main green in a monorepo
  5. Researchers describe how to tell if ChatGPT is confabulating

    …[T]he researchers focus on what they call semantic entropy. This evaluates all the statistically likely answers evaluated by the LLM and determines how many of them are semantically equivalent. If a large number all have the same meaning, then the LLM is likely uncertain about phrasing but has the right answer. If not, then it is presumably in a situation where it would be prone to confabulation and should be prevented from doing so.