Entity Embeddings : Perspectives Towards an Omni-Modality Era for Large Language Models
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ID: 283370
2023
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Abstract
Large Language Models (LLMs) are evolving to integrate multiple modalities,
such as text, image, and audio into a unified linguistic space. We envision a
future direction based on this framework where conceptual entities defined in
sequences of text can also be imagined as modalities. Such a formulation has
the potential to overcome the cognitive and computational limitations of
current models. Several illustrative examples of such potential implicit
modalities are given. Along with vast promises of the hypothesized structure,
expected challenges are discussed as well.
| Reference Key |
ciftci2023entity
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|---|---|
| Authors | Eren Unlu; Unver Ciftci |
| Journal | arXiv |
| Year | 2023 |
| DOI |
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