113 citations · 120 across the 7 of their papers we have counts for
7 papers
A Unified Evaluation Framework for Novelty Detection and Accommodation in NLP with an Instantiation in Authorship Attribution
Neeraj Varshney, Himanshu Gupta, Eric Robertson +2
State-of-the-art natural language processing models have been shown to achieve remarkable performance in 'closed-world' settings where all the labels in the evaluation set are know…
Human Activity Recognition in an Open World
Derek S. Prijatelj, Samuel Grieggs, Jin Huang +6
Managing novelty in perception-based human activity recognition (HAR) is critical in realistic settings to improve task performance over time and ensure solution generalization out…
Semantic Novelty Detection and Characterization in Factual Text Involving Named Entities
Nianzu Ma, Sahisnu Mazumder, Alexander Politowicz +3
Much of the existing work on text novelty detection has been studied at the topic level, i.e., identifying whether the topic of a document or a sentence is novel or not. Little wor…
AI Autonomy : Self-Initiated Open-World Continual Learning and Adaptation
Bing Liu, Sahisnu Mazumder, Eric Robertson +1
As more and more AI agents are used in practice, it is time to think about how to make these agents fully autonomous so that they can (1) learn by themselves continually in a self-…
Self-Initiated Open World Learning for Autonomous AI Agents
Bing Liu, Eric Robertson, Scott Grigsby +1
As more and more AI agents are used in practice, it is time to think about how to make these agents fully autonomous so that they can learn by themselves in a self-motivated and se…
Zero-Shot Out-of-Distribution Detection Based on the Pre-trained Model CLIP
Sepideh Esmaeilpour, Bing Liu, Eric Robertson +1
In an out-of-distribution (OOD) detection problem, samples of known classes(also called in-distribution classes) are used to train a special classifier. In testing, the classifier…
Handwriting Recognition with Novelty
Derek S. Prijatelj, Samuel Grieggs, Futoshi Yumoto +2
This paper introduces an agent-centric approach to handle novelty in the visual recognition domain of handwriting recognition (HWR). An ideal transcription agent would rival or sur…