LLM cross-model alignment measurement and improvement
It has been shown that independently trained LLMs (GPT, BERT, etc) learn input vector representations that have a certain structure, similar between the different models. The aim of this thesis is to measure this similarity (or "alignment") between pre-trained models, in-training models and possibly integrate alignment into the training process as an optimization objective.
Graduation Theses defence year
Spoken language (s)
Requirements for candidates
Python, pytorch, transformers, vector space transformations and metrics
Application of contact