38 citations · 159 across the 19 of their papers we have counts for
7 papers · 1 filter
One-Versus-Others Attention: Scalable Multimodal Integration for Biomedical Data
Michal Golovanevsky, Eva Schiller, Akira Nair +3
Multimodal learning models have become increasingly important as they surpass single-modality approaches on diverse tasks ranging from question-answering to autonomous driving. Des…
Neural Summarization of Electronic Health Records
Koyena Pal, Seyed Ali Bahrainian, Laura Mercurio +1
Hospital discharge documentation is among the most essential, yet time-consuming documents written by medical practitioners. The objective of this study was to automatically genera…
Stable Anisotropic Regularization
William Rudman, Carsten Eickhoff
Given the success of Large Language Models (LLMs), there has been considerable interest in studying the properties of model activations. The literature overwhelmingly agrees that L…
Language Models Implement Simple Word2Vec-style Vector Arithmetic
Jack Merullo, Carsten Eickhoff, Ellie Pavlick
A primary criticism towards language models (LMs) is their inscrutability. This paper presents evidence that, despite their size and complexity, LMs sometimes exploit a simple vect…
Enhancing the Ranking Context of Dense Retrieval Methods through Reciprocal Nearest Neighbors
George Zerveas, Navid Rekabsaz, Carsten Eickhoff
Sparse annotation poses persistent challenges to training dense retrieval models; for example, it distorts the training signal when unlabeled relevant documents are used spuriously…
Parameter-efficient Modularised Bias Mitigation via AdapterFusion
Deepak Kumar, Oleg Lesota, George Zerveas +4
Large pre-trained language models contain societal biases and carry along these biases to downstream tasks. Current in-processing bias mitigation approaches (like adversarial train…