Summary of Geotokens and Geotransformers, by Eren Unlu
Geotokens and Geotransformers
by Eren Unlu
First submitted to arxiv on: 23 Mar 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 proposes geotokens, a new type of input component for transformer architectures that incorporates geographical locations. Unlike traditional language sequences, the order of these tokens is not as crucial as their corresponding coordinates. To address this challenge, the authors develop a position encoding approach inspired by Rotary Position Embedding (RoPE), but adapted for spherical coordinates. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper creates special words called geotokens that connect to specific places on Earth. Instead of the order of these words being important, it’s more about where they are located. To help with this, the researchers design a new way to understand position using ideas from RoPE and geography. |
Keywords
* Artificial intelligence * Embedding * Transformer
