4 papers · 1 filter
Understanding Submodular Information Measure Based Objectives for Representation Learning: A Variance and Separation Perspective
Rishabh Iyer, Truong Pham, Anay Majee
Submodular Information Measures (SIMs) have recently emerged as a powerful framework for representation learning and multimodal learning. In particular, the SCORE framework~\cite{m…
InSQuAD: In-Context Learning for Efficient Retrieval via Submodular Mutual Information to Enforce Quality and Diversity
Souradeep Nanda, Anay Majee, Rishabh Iyer
In this paper, we introduce InSQuAD, designed to enhance the performance of In-Context Learning (ICL) models through Submodular Mutual Information} (SMI) enforcing Quality and Dive…
STENCIL: Submodular Mutual Information Based Weak Supervision for Cold-Start Active Learning
Nathan Beck, Adithya Iyer, Rishabh Iyer
As supervised fine-tuning of pre-trained models within NLP applications increases in popularity, larger corpora of annotated data are required, especially with increasing parameter…
Theoretical Analysis of Submodular Information Measures for Targeted Data Subset Selection
Nathan Beck, Truong Pham, Rishabh Iyer
With increasing volume of data being used across machine learning tasks, the capability to target specific subsets of data becomes more important. To aid in this capability, the re…