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Found 6 papers, 2 papers with code
Reinforcement Learning with Dynamic Multi-Reward Weighting for Multi-Style Controllable Generation
Style is an integral component of text that expresses a diverse set of information, including interpersonal dynamics (e. g. formality) and the author's emotions or attitudes (e. g. disgust).
Under the Surface: Tracking the Artifactuality of LLM-Generated Data
This work delves into the expanding role of large language models (LLMs) in generating artificial data.
An Analysis of Reader Engagement in Literary Fiction through Eye Tracking and Linguistic Features
Capturing readers' engagement in fiction is a challenging but important aspect of narrative understanding.
infoVerse: A Universal Framework for Dataset Characterization with Multidimensional Meta-information
However, not all samples in these datasets are equally valuable for learning, as some may be redundant or noisy.
A Comparative Study on Textual Saliency of Styles from Eye Tracking, Annotations, and Language Models
We develop a variety of methods to derive style saliency scores over text using the collected eye dataset.
An Analysis of Deep Object Detectors For Diver Detection
We evaluate these networks on typical accuracy and efficiency metrics, as well as on the temporal stability of their detections.
