Machine Learning

1 readers

1 users here now

Community Rules:

Be nice. No offensive behavior, insults or attacks: we encourage a diverse community in which members feel safe and have a voice.
Make your post clear and comprehensive: posts that lack insight or effort will be removed. (ex: questions which are easily googled)
Beginner or career related questions go elsewhere. This community is focused in discussion of research and new projects that advance the state-of-the-art.
Limit self-promotion. Comments and posts should be first and foremost about topics of interest to ML observers and practitioners. Limited self-promotion is tolerated, but the sub is not here as merely a source for free advertisement. Such posts will be removed at the discretion of the mods.

founded 11 months ago

MODERATORS

communick@academy.garden

[D] Efficient ways to achieve Multi modality in LLMs (alien.top)

submitted 9 months ago by Infamous-Belt8671@alien.top to c/machinelearning@academy.garden

2 comments fedilink hide all child comments

What is the best approach to achieve multi modality using a instruct fine tuned model?

you are viewing a single comment's thread
view the rest of the comments

[–] DeliciousFriedPanda@alien.top 1 points 9 months ago

The field is broad, with no easy answer and many nuances, you could fill countless PostDocs and Phds with work here.

Judging by the way you phrased your question, very generically and without essentially any detail, I'm going to take a wild guess and say that you're either a beginner in ML ot haven't read/studied anything on the subject.

I'd encourage you to start by reading recent and not-so-recent papers dealing with inherently multimodal tasks, like scene text recognition, VQA, and the like. The big problem in the field is that the models will, generally speaking, try to overfit on the modality that's mostly information-dense between V and L for your task. In current SoTa methods, the best way to mitigate this seems to be fusing the two modalities via a gradual mechanism, for example the gated tanh attention of Flamingo.

Happy reading!