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Skip to Search Results- 27Natural Language Processing
- 11Machine Learning
- 9Bioinformatics
- 5Artificial Intelligence
- 3NLP
- 3Reinforcement Learning
- 1Alexander, Graham
- 1Bandi Kenari, Nahid
- 1Campbell, Hazel V
- 1Costello, Jeremy
- 1Damavandi, Babak
- 1Dhankar, Abhishek
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Investigation of Causal Mutations in Livestock and Companion Animals Using Whole-Genome Sequencing (WGS) and Bioinformatics
DownloadSpring 2024
In this thesis project, three studies were conducted, aimed at identifying the causal variants responsible for phenotypic/genotypic sex discordance in cattle, copper toxicosis in Dalmatian dogs, and low fertility/infertility in cattle. In all three studies, whole-genome sequencing (WGS) and...
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Spring 2024
We introduce the background of the natural language processing field, outlining the benefits and drawbacks of rule-based versus statistical methods. We present knowledge graphs as a way to integrate the explainability of rule-based methods and the power of statistical methods, large language...
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Spring 2024
In the era of artificial intelligence, neural models have emerged as a powerful tool for tackling a wide range of tasks. However, these models are commonly regarded as black-box systems, making it difficult to understand their internal workings. The natural language explanation task seeks to...
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Fall 2023
This thesis introduces a new approach for grounding concepts to vision using visual descriptions, which are text-based descriptions of visual attributes. We hypothesize that these descriptions can enhance the grounding of concepts to vision, thereby improving performance in vision-language tasks....
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Vision-assisted behavior-based construction safety: Integrating computer vision and natural language processing
DownloadFall 2023
Background: Construction sites can be hazardous places. Behavior-based safety is a method to optimize workers’ behaviors and improve site safety. Previous behavior-based safety has been criticized for their low efficiency because of manual observation. The community has conducted enormous studies...
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Fall 2023
Explainable artificial intelligence models are becoming increasingly important as restrictions grow for corporate use of blackbox models whose predictions affect people’s lives and yet cannot be interpreted. Black boxes do not convey trust to end-users and are difficult to train and debug for...
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Spring 2023
This thesis describes the design of a system that is capable of the generation of a Knowledge Graph (KG), referred to as Knowledge Graph Population (KGP), from conversations, specifically with elderly people. While this system still follows a traditional KGP approach with Entity Recognition (ER),...
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Spring 2023
The gaming industry has experienced a sharp growth in recent years, surpassing other popular entertainment segments, such as the film industry. With the ever-increasing scale of the gaming industry and the fact that players are extremely difficult to satisfy, it has become extremely challenging...
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Spring 2023
Dialogue systems powered by large pre-trained language models exhibit an innate ability to deliver fluent and natural-sounding responses. Despite their impressive performance, these models fail to conduct interesting and consistent exchanges of turns and can often generate factually incorrect...
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An Exploration of Dialog Act Classification in Open-domain Conversational Agents and the Applicability of Text Data Augmentation
DownloadFall 2023
Recognizing dialog acts of users is an essential component in building successful conversational agents. In this work, we propose a dialog act (DA) classifier for two of our open domain conversational agents. For this, we curated a high-quality, multi-domain dataset with ∼24k user utterances...