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Found 11 papers, 2 papers with code
A Test Suite and Manual Evaluation of Document-Level NMT at WMT19
As the quality of machine translation rises and neural machine translation (NMT) is moving from sentence to document level translations, it is becoming increasingly difficult to evaluate the output of translation systems.
Debiasing Algorithm through Model Adaptation
Large language models are becoming the go-to solution for the ever-growing number of tasks.
Examining Structure of Word Embeddings with PCA
We also show that further examining histograms of classes along the principal component is important to understand the structure of representation of information in embeddings.
Derivational Morphological Relations in Word Embeddings
Derivation is a type of a word-formation process which creates new words from existing ones by adding, changing or deleting affixes.
Semantic Holism and Word Representations in Artificial Neural Networks
Taking Tugendhat's formal reinterpretation of Frege's work as a starting point, we demonstrate that it is analogical to the process of training the Skip-gram model and offers a possible explanation of its semantic properties.
THEaiTRE: Artificial Intelligence to Write a Theatre Play
We present THEaiTRE, a starting project aimed at automatic generation of theatre play scripts.
Measuring Memorization Effect in Word-Level Neural Networks Probing
In classical probing, a classifier is trained on the representations to extract the target linguistic information.
THEaiTRE 1.0: Interactive generation of theatre play scripts
We present the first version of a system for interactive generation of theatre play scripts.
DialogueScript: Using Dialogue Agents to Produce a Script
We present a novel approach to generating scripts by using agents with different personality types.
GPT-2-based Human-in-the-loop Theatre Play Script Generation
We experiment with adapting generative language models for the generation of long coherent narratives in the form of theatre plays.
Independent Components of Word Embeddings Represent Semantic Features
Independent Component Analysis (ICA) is an algorithm originally developed for finding separate sources in a mixed signal, such as a recording of multiple people in the same room speaking at the same time.
