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Foundation models serve as the backbone for numerous specialized models developed through fine-tuning. However, when the underlying …

Evolutionary model merging enables the creation of high-performing multi-task models but remains computationally prohibitive for …

Task Arithmetic has emerged as a simple yet effective method to merge models without additional training. However, by treating entire …

In this paper, we present a novel data-free method for merging neural networks in weight space. Differently from most existing works, …

Getting a good understanding of the user intent is vital for e-commerce applications to surface the right product to a given customer …

Datasets used to train deep learning models in industrial settings often exhibit skewed distributions with some samples repeated a …

Few-shot graph classification is a novel yet promising emerging research field that still lacks the soundness of well-established …

Cross-lingual phenomena are quite common in informal contexts like social media, where users are likely to mix their native language …