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Skip to Search Results- 3Machine Learning
- 2Contrastive Learning
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- 1Aspect Based Sentiment Analysis
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Computing Emotion Dynamics from Text and Exploring their use as Biosocial Markers of Overall Well-being
DownloadFall 2023
Language is inherently social -- it is influenced by our lived experiences and environments, and impacts the way in which we communicate with each other. Therefore, it is not a surprise that our health impacts our language. The patterns with which emotion changes over time -- emotion dynamics --...
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Fall 2024
This thesis presents a novel data-driven approach for identifying categoryselective regions in the human brain that are consistent across multiple participants. By leveraging a massive fMRI dataset and a multi-modal (language and image) neural network (CLIP), we trained a highly accurate...
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Exploring Methods for Generating and Evaluating Skill Targeted Reading Comprehension Questions
DownloadSpring 2024
It takes skilled teachers a significant amount of time and effort to create high quality reading comprehension questions, often making it impractical to target a particular reader’s weaknesses. Recently, language models have been proposed as a tool to help teachers fill this gap, allowing these...
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Fall 2021
The representations generated by many models of language (word embeddings, recurrent neural networks and transformers) correlate to brain activity recorded while people listen. However, these decoding results are usually based on the brain’s reaction to syntactically and semantically sound...
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Insights into Early Word Comprehension - Tracking the Neural Representations of Word Semantics in Infants
DownloadSpring 2022
Infants start developing rudimentary language skills and can start understanding simple words well before their first birthday. This development has also been shown primarily using Event Related Potential (ERP) techniques to find evidence of word comprehension in the infant brain. While these...
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Fall 2021
The performance of reinforcement learning (RL) agents is sensitive to the choice of hyperparameters. In real-world settings like robotics or industrial control systems, however, testing different hyperparameter configurations directly on the environment can be financially prohibitive, dangerous,...
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Fall 2020
Language Modeling (LM) is often formulated as a next-word prediction problem over a large vocabulary, which makes it challenging. To effectively perform the task of next-word prediction, Long Short Term Memory networks (LSTMs) must keep track of many types of information. Some information is...
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Studying Limitations of Generative Transformer based models for Aspect Based Sentiment Analysis
DownloadSpring 2023
Companies can only progress if they understand what their customers feel about their products and services. With companies having an online presence, and with the availability of third-party online reviewing platforms like Yelp, it becomes critical to scour through online reviews. Analysing...
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The Contrastive Gap: A New Perspective on the ‘Modality Gap’ in Multimodal Contrastive Learning
DownloadFall 2024
Learning jointly from images and texts using contrastive pre-training has emerged as an effective method to train large-scale models with a strong grasp of semantic image concepts. For instance, CLIP, pre-trained on a large corpus of web data, excels in tasks like zero-shot image classification,...