Search Results for author:
Found 9 papers, 5 papers with code
TopGuNN: Fast NLP Training Data Augmentation using Large Corpora
Acquiring training data for natural language processing systems can be expensive and time-consuming.
DataDreamer: A Tool for Synthetic Data Generation and Reproducible LLM Workflows
The rapid rise to prominence of these models and these unique challenges has had immediate adverse impacts on open science and on the reproducibility of work that uses them.
ParaGuide: Guided Diffusion Paraphrasers for Plug-and-Play Textual Style Transfer
Our parameter-efficient approach, ParaGuide, leverages paraphrase-conditioned diffusion models alongside gradient-based guidance from both off-the-shelf classifiers and strong existing style embedders to transform the style of text while preserving semantic information.
Learning Interpretable Style Embeddings via Prompting LLMs
Style representation learning builds content-independent representations of author style in text.
Leveraging Large Language Models in Conversational Recommender Systems
A Conversational Recommender System (CRS) offers increased transparency and control to users by enabling them to engage with the system through a real-time multi-turn dialogue.
Low-Resource Authorship Style Transfer: Can Non-Famous Authors Be Imitated?
Existing unsupervised approaches like STRAP have largely focused on style transfer to target authors with many examples of their writing style in books, speeches, or other published works.
Bidirectional Language Models Are Also Few-shot Learners
An arbitrary task can be reformulated as a natural language prompt, and a language model can be asked to generate the completion, indirectly performing the task in a paradigm known as prompt-based learning.
Multilingual Bidirectional Unsupervised Translation Through Multilingual Finetuning and Back-Translation
We propose a two-stage approach for training a single NMT model to translate unseen languages both to and from English.
Magnitude: A Fast, Efficient Universal Vector Embedding Utility Package
Vector space embedding models like word2vec, GloVe, fastText, and ELMo are extremely popular representations in natural language processing (NLP) applications.
