2 papers
cs.IR2026
TokenMinds: Pretrained User Tokens and Embeddings for User Understanding in Large Recommender Systems
Qingyun Liu, Bo Yan, Yang Liu +15
User modeling in industrial recommender systems typically produces dense embeddings, which suffer from representational constraints inherent to fixed-dimensional vectors. An emergi…
cs.LG2024
The Non-Local Model Merging Problem: Permutation Symmetries and Variance Collapse
Ekansh Sharma, Daniel M. Roy, Gintare Karolina Dziugaite
Model merging aims to efficiently combine the weights of multiple expert models, each trained on a specific task, into a single multi-task model, with strong performance across all…