Row 27766
Content Data
This page contains data entry 27766 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.
On a related note, I wonder how much these models differentiate the positional encoding component of embeddings from the rest of the embedding? Does the positional enoding ever get updated/transformed in same way as rest of the embedding?
I assume image embeddings, representing parts of the image, also contain (2-D) positional encodings to allow the model to reason about relative positions ?
| Field | Value |
|---|---|
| text | On a related note, I wonder how much these models differentiate the positional encoding component of embeddings from the rest of the embedding? Does the positional enoding ever get updated/transformed in same way as rest of the embedding? I assume image embeddings, representing parts of the image, also contain (2-D) positional encodings to allow the model to reason about relative positions ? |
| label | r/machinelearning |
| dataType | comment |
| communityName | r/MachineLearning |
| datetime | 2024-05-21 |
| username_encoded | Z0FBQUFBQm5Lak1FODdWM3J4MjhIdE1VVFFaUjU0dXQ0VjBiQVlQWmFQdVhWQlRkMTRteEdlakVHZzRZVFJWUm80akk5NmZXMk04elNWVnVXODNuS2lMQnlBOVFHWU53RXc9PQ== |
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Raw Record
{
"text": "On a related note, I wonder how much these models differentiate the positional encoding component of embeddings from the rest of the embedding? Does the positional enoding ever get updated/transformed in same way as rest of the embedding?\n\nI assume image embeddings, representing parts of the image, also contain (2-D) positional encodings to allow the model to reason about relative positions ?",
"label": "r/machinelearning",
"dataType": "comment",
"communityName": "r/MachineLearning",
"datetime": "2024-05-21",
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}
Entry Information
- Entry ID: 27766
- Repository: Axioma AXP
- Dataset: arrmlet/reddit_dataset_36
- Total Entries: 100,000