20 citations · 29 across the 4 of their papers we have counts for
5 papers
Closing the Context Gap: Activation Alignment for Tabular In-Context Learning
Yoel Zeldes
Tabular foundation models perform in-context learning (ICL) by conditioning predictions on labeled training examples provided as context. Unlike traditional models that separate tr…
ComMer: a Framework for Compressing and Merging User Data for Personalization
Yoel Zeldes, Amir Zait, Ilia Labzovsky +2
Large Language Models (LLMs) excel at a wide range of tasks, but adapting them to new data, particularly for personalized applications, poses significant challenges due to resource…
Standing on the Shoulders of Giant Frozen Language Models
Yoav Levine, Itay Dalmedigos, Ori Ram +10
Huge pretrained language models (LMs) have demonstrated surprisingly good zero-shot capabilities on a wide variety of tasks. This gives rise to the appealing vision of a single, ve…
Technical Report: Auxiliary Tuning and its Application to Conditional Text Generation
Yoel Zeldes, Dan Padnos, Or Sharir +1
We introduce a simple and efficient method, called Auxiliary Tuning, for adapting a pre-trained Language Model to a novel task; we demonstrate this approach on the task of conditio…
Deep density networks and uncertainty in recommender systems
Yoel Zeldes, Stavros Theodorakis, Efrat Solodnik +3
Building robust online content recommendation systems requires learning complex interactions between user preferences and content features. The field has evolved rapidly in recent…