Search Results for author:
Found 12 papers, 3 papers with code
GANDALF: a General Character Name Description Dataset for Long Fiction
This paper introduces a long-range multiple-choice Question Answering (QA) dataset, based on full-length fiction book texts.
Lessons Learned from GPT-SW3: Building the First Large-Scale Generative Language Model for Swedish
We present GTP-SW3, a 3. 5 billion parameter autoregressive language model, trained on a newly created 100 GB Swedish corpus.
GPT-SW3: An Autoregressive Language Model for the Nordic Languages
This paper details the process of developing the first native large generative language model for the Nordic languages, GPT-SW3.
The Nordic Pile: A 1.2TB Nordic Dataset for Language Modeling
Pre-training Large Language Models (LLMs) require massive amounts of text data, and the performance of the LLMs typically correlates with the scale and quality of the datasets.
A comparative evaluation and analysis of three generations of Distributional Semantic Models
In this paper, we perform a comprehensive evaluation of type distributional vectors, either produced by static DSMs or obtained by averaging the contextualized vectors generated by BERT.
Deep Representational Re-tuning using Contrastive Tension
Extracting semantically useful natural language sentence representations from pre-trained deep neural networks such as Transformers remains a challenge.
SenseCluster at SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection
We (Team Skurt) propose a simple method to detect lexical semantic change by clustering contextualized embeddings produced by XLM-R, using K-Means++.
Measuring Issue Ownership using Word Embeddings
Sentiment and topic analysis are common methods used for social media monitoring.
R-grams: Unsupervised Learning of Semantic Units in Natural Language
This paper investigates data-driven segmentation using Re-Pair or Byte Pair Encoding-techniques.
Distributional Term Set Expansion
This paper is a short empirical study of the performance of centrality and classification based iterative term set expansion methods for distributional semantic models.
The Gavagai Living Lexicon
This paper presents the Gavagai Living Lexicon, which is an online distributional semantic model currently available in 20 different languages.
Navigating the Semantic Horizon using Relative Neighborhood Graphs
We also argue that the topology of the neighborhoods in semantic space can be used to determine the semantic horizon of a point, which we define as the set of neighbors that have a direct connection to the point.
