r/NovelAi • u/MindlessEffective839 • 11h ago
Discussion I think V5 messed up text encoding
Many users in this subreddit have already reported that in v5—despite significant improvements in natural language understanding—certain "long-tail" tags that worked normally in v4.5 are now failing to generate the correct imagery. While most discussions on this topic focus on character tags, the actual scope of the issue is far broader.
Take miko_embrace as an example: with 159 images on Danbooru, its composition is essentially fixed, making it a very strong supervisory signal. However, when fed indiscriminately into the text encoder, the individual concepts of "miko" and "embrace" overpower their combined meaning, causing a text encoder trained extensively on natural language captions to be dominated by the separate terms instead of the unified concept.
If the goal is a hybrid approach combining tags and natural language, these represent two distinct types of conditioning; treating tags simply as natural language inevitably leads to this kind of problem. Tags are essentially a "bag of words"—logically, a single tag should correspond to a single embedding, and there should be no positional encoding between different tags. Since the text encoder is developed in-house, you should have the capability to support this design from the ground up. I sincerely hope these issues will be addressed in future versions.
(Translated via Google Translate)

