20 citations · 43 across the 14 of their papers we have counts for
14 papers
Image-Text Relation Prediction for Multilingual Tweets
Matīss Rikters, Edison Marrese-Taylor
Various social networks have been allowing media uploads for over a decade now. Still, it has not always been clear what is their relation with the posted text or even if there is…
Annotations for Exploring Food Tweets From Multiple Aspects
Matīss Rikters, Edison Marrese-Taylor, Rinalds Vīksna
This research builds upon the Latvian Twitter Eater Corpus (LTEC), which is focused on the narrow domain of tweets related to food, drinks, eating and drinking. LTEC has been colle…
Strategic Insights in Human and Large Language Model Tactics at Word Guessing Games
Matīss Rikters, Sanita Reinsone
At the beginning of 2022, a simplistic word-guessing game took the world by storm and was further adapted to many languages beyond the original English version. In this paper, we e…
What Food Do We Tweet about on a Rainy Day?
Maija Kāle, Matīss Rikters
Food choice is a complex phenomenon shaped by factors such as taste, ambience, culture or weather. In this paper, we explore food-related tweeting in different weather conditions.…
How Masterly Are People at Playing with Their Vocabulary? Analysis of the Wordle Game for Latvian
Matīss Rikters, Sanita Reinsone
In this paper, we describe adaptation of a simple word guessing game that occupied the hearts and minds of people around the world. There are versions for all three Baltic countrie…
Revisiting Context Choices for Context-aware Machine Translation
Matīss Rikters, Toshiaki Nakazawa
One of the most popular methods for context-aware machine translation (MT) is to use separate encoders for the source sentence and context as multiple sources for one target senten…
Fragmented and Valuable: Following Sentiment Changes in Food Tweets
Maija Kāle, Matīss Rikters
We analysed sentiment and frequencies related to smell, taste and temperature expressed by food tweets in the Latvian language. To get a better understanding of the role of smell,…
Document-aligned Japanese-English Conversation Parallel Corpus
Matīss Rikters, Ryokan Ri, Tong Li +1
Sentence-level (SL) machine translation (MT) has reached acceptable quality for many high-resourced languages, but not document-level (DL) MT, which is difficult to 1) train with l…
What Can We Learn From Almost a Decade of Food Tweets
Uga Sproģis, Matīss Rikters
We present the Latvian Twitter Eater Corpus - a set of tweets in the narrow domain related to food, drinks, eating and drinking. The corpus has been collected over time-span of ove…
Designing the Business Conversation Corpus
Matīss Rikters, Ryokan Ri, Tong Li +1
While the progress of machine translation of written text has come far in the past several years thanks to the increasing availability of parallel corpora and corpora-based trainin…
Impact of Corpora Quality on Neural Machine Translation
Matīss Rikters
Large parallel corpora that are automatically obtained from the web, documents or elsewhere often exhibit many corrupted parts that are bound to negatively affect the quality of th…
Debugging Neural Machine Translations
Matīss Rikters
In this paper, we describe a tool for debugging the output and attention weights of neural machine translation (NMT) systems and for improved estimations of confidence about the ou…
Confidence through Attention
Matīss Rikters, Mark Fishel
Attention distributions of the generated translations are a useful bi-product of attention-based recurrent neural network translation models and can be treated as soft alignments b…
Paying Attention to Multi-Word Expressions in Neural Machine Translation
Matīss Rikters, Ondřej Bojar
Processing of multi-word expressions (MWEs) is a known problem for any natural language processing task. Even neural machine translation (NMT) struggles to overcome it. This paper…