Summary of What We Talk About When We Talk About Lms: Implicit Paradigm Shifts and the Ship Of Language Models, by Shengqi Zhu and Jeffrey M. Rzeszotarski
What We Talk About When We Talk About LMs: Implicit Paradigm Shifts and the Ship of Language Models
by Shengqi Zhu, Jeffrey M. Rzeszotarski
First submitted to arxiv on: 2 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 This paper investigates the phenomenon of language models as a constantly evolving concept in natural language processing (NLP). It proposes a novel perspective on scientific progress by examining how existing terms are continuously updated through implicit retrofits. The authors construct a data infrastructure based on recent NLP publications and perform text-based analyses to quantify the use of language models as a term of art. The study highlights the interplay between systems and theories in scientific discourse, emphasizing the need for attention to the transformation of this concept. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about how our understanding of language models in computers is always changing. It’s like a big ship that gets new parts added or replaced over time, but it still remains the same ship. The researchers built a special database using recent papers on computer language and did some analysis to understand how people use this concept. They found that ideas and systems influence each other in scientific discussions, and we should pay attention to how our understanding of language models evolves. |
Keywords
» Artificial intelligence » Attention » Discourse » Natural language processing » Nlp
