Summary of On Behalf Of the Stakeholders: Trends in Nlp Model Interpretability in the Era Of Llms, by Nitay Calderon et al.
On Behalf of the Stakeholders: Trends in NLP Model Interpretability in the Era of LLMs
by Nitay Calderon, Roi Reichart
First submitted to arxiv on: 27 Jul 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Recent advancements in Natural Language Processing (NLP) systems, particularly Large Language Models (LLMs), have led to widespread adoption across domains, impacting decision-making, job markets, society, and scientific research. This surge in usage has driven research on NLP model interpretability and analysis. However, existing surveys often overlook the needs and perspectives of explanation stakeholders. To address this gap, we explore three fundamental questions: Why do we need interpretability, what are we interpreting, and how? We examine existing interpretability paradigms, their properties, and relevance to different stakeholders. Our analysis reveals significant disparities between NLP developers and non-developer users, as well as between research fields, highlighting the diverse needs of stakeholders. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about understanding how computers can explain what they’ve learned from language data. Computers are getting very good at talking to us in our own language, which has big implications for decision-making and society. But before we can really use these computers effectively, we need to understand why they’re saying certain things and how they came up with those answers. The paper looks at different ways that computer models can be explained and finds that what works for one group of people might not work for another. For example, some people just want to know what a model is saying, while others want to see inside the model’s “brain” to understand how it made its decisions. |
Keywords
» Artificial intelligence » Natural language processing » Nlp
