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Found 10 papers, 1 papers with code
Towards Coding Social Science Datasets with Language Models
This provides exciting evidence that language models can serve as a critical advance in the coding of open-ended texts in a variety of applications.
Out of One, Many: Using Language Models to Simulate Human Samples
We propose and explore the possibility that language models can be studied as effective proxies for specific human sub-populations in social science research.
Data-adaptive Transfer Learning for Translation: A Case Study in Haitian and Jamaican
Our experiments suggest that for some languages beyond a threshold of authentic data, back-translation augmentation methods are counterproductive, while cross-lingual transfer from a sufficiently related language is preferred.
An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labels
Pre-trained language models derive substantial linguistic and factual knowledge from the massive corpora on which they are trained, and prompt engineering seeks to align these models to specific tasks.
Towards Neural Programming Interfaces
It is notoriously difficult to control the behavior of artificial neural networks such as generative neural language models.
Machine Learning for Offensive Security: Sandbox Classification Using Decision Trees and Artificial Neural Networks
The merits of machine learning in information security have primarily focused on bolstering defenses.
Can Humor Prediction Datasets be used for Humor Generation? Humorous Headline Generation via Style Transfer
Understanding and identifying humor has been increasingly popular, as seen by the number of datasets created to study humor.
Linguistic Embeddings as a Common-Sense Knowledge Repository: Challenges and Opportunities
Many applications of linguistic embedding models rely on their value as pre-trained inputs for end-to-end tasks such as dialog modeling, machine translation, or question answering.
Embedding Grammars
Classic grammars and regular expressions can be used for a variety of purposes, including parsing, intent detection, and matching.
What can you do with a rock? Affordance extraction via word embeddings
Autonomous agents must often detect affordances: the set of behaviors enabled by a situation.
