11 citations · 34 across the 9 of their papers we have counts for
9 papers
Unsupervised Text Representation Learning via Instruction-Tuning for Zero-Shot Dense Retrieval
Qiuhai Zeng, Zimeng Qiu, Dae Yon Hwang +2
Dense retrieval systems are commonly used for information retrieval (IR). They rely on learning text representations through an encoder and usually require supervised modeling via…
Efficient Semi-Supervised Learning for Natural Language Understanding by Optimizing Diversity
Eunah Cho, He Xie, John P. Lalor +2
Expanding new functionalities efficiently is an ongoing challenge for single-turn task-oriented dialogue systems. In this work, we explore functionality-specific semi-supervised le…
Making Sense of Unstructured Text Data
Lin Li, William M. Campbell, Cagri Dagli +1
Many network analysis tasks in social sciences rely on pre-existing data sources that were created with explicit relations or interactions between entities under consideration. Exa…
Graph Model Selection via Random Walks
Lin Li, William M. Campbell, Rajmonda S. Caceres
In this paper, we present a novel approach based on the random walk process for finding meaningful representations of a graph model. Our approach leverages the transient behavior o…
Consistent Alignment of Word Embedding Models
Cem Safak Sahin, Rajmonda S. Caceres, Brandon Oselio +1
Word embedding models offer continuous vector representations that can capture rich contextual semantics based on their word co-occurrence patterns. While these word vectors can pr…
Model Selection Framework for Graph-based data
Rajmonda S. Caceres, Leah Weiner, Matthew C. Schmidt +2
Graphs are powerful abstractions for capturing complex relationships in diverse application settings. An active area of research focuses on theoretical models that define the gener…