Simen
@eide.ai
AI statistician (is that something?) building algorithms for Schibsted news media during daytime, outdoors and always injured during other times. Based in Norway. Not sure what ill do here yet
Trying @perplexitycomet.bsky.social and testing the first "agentic" suggestion. You cant make this up.
September 30, 2025 at 7:48 PM
Trying @perplexitycomet.bsky.social and testing the first "agentic" suggestion. You cant make this up.
The added benefit of being bayesian here is that tasks with less data will be more similar to the hierarchical mean parameter set Θ. And therefore learn from other tasks!
November 25, 2024 at 2:36 PM
The added benefit of being bayesian here is that tasks with less data will be more similar to the hierarchical mean parameter set Θ. And therefore learn from other tasks!
It works by constructing a hierarchical LLM where each task adapter parameter set θ_d has a prior to a shared hierarchical mean parameter set Θ.
November 25, 2024 at 2:36 PM
It works by constructing a hierarchical LLM where each task adapter parameter set θ_d has a prior to a shared hierarchical mean parameter set Θ.
New finetuning method: Bayesian Hierarchical LoRa (BORA) (arxiv.org/abs/2407.15857)
If you have multiple and similar LLM tasks you want to finetune, you should share knowledge between the different adapters when training, and we show how using Bayesian Hierarchical modelling
If you have multiple and similar LLM tasks you want to finetune, you should share knowledge between the different adapters when training, and we show how using Bayesian Hierarchical modelling
November 25, 2024 at 2:36 PM
New finetuning method: Bayesian Hierarchical LoRa (BORA) (arxiv.org/abs/2407.15857)
If you have multiple and similar LLM tasks you want to finetune, you should share knowledge between the different adapters when training, and we show how using Bayesian Hierarchical modelling
If you have multiple and similar LLM tasks you want to finetune, you should share knowledge between the different adapters when training, and we show how using Bayesian Hierarchical modelling
