42 citations · 110 across the 36 of their papers we have counts for
8 papers · 2 filters
An Empirical study of Unsupervised Neural Machine Translation: analyzing NMT output, model's behavior and sentences' contribution
Isidora Chara Tourni, Derry Wijaya
Unsupervised Neural Machine Translation (UNMT) focuses on improving NMT results under the assumption there is no human translated parallel data, yet little work has been done so fa…
Relevance-guided Neural Machine Translation
Isidora Chara Tourni, Derry Wijaya
With the advent of the Transformer architecture, Neural Machine Translation (NMT) results have shown great improvement lately. However, results in low-resource conditions still lag…
COVID-19 Vaccine Misinformation in Middle Income Countries
Jongin Kim, Byeo Rhee Bak, Aditya Agrawal +4
This paper introduces a multilingual dataset of COVID-19 vaccine misinformation, consisting of annotated tweets from three middle-income countries: Brazil, Indonesia, and Nigeria.…
DUnE: Dataset for Unified Editing
Afra Feyza Akyürek, Eric Pan, Garry Kuwanto +1
Even the most advanced language models remain susceptible to errors necessitating to modify these models without initiating a comprehensive retraining process. Model editing refers…
Explain-then-Translate: An Analysis on Improving Program Translation with Self-generated Explanations
Zilu Tang, Mayank Agarwal, Alex Shypula +4
This work explores the use of self-generated natural language explanations as an intermediate step for code-to-code translation with language models. Across three types of explanat…
Replicable Benchmarking of Neural Machine Translation (NMT) on Low-Resource Local Languages in Indonesia
Lucky Susanto, Ryandito Diandaru, Adila Krisnadhi +2
Neural machine translation (NMT) for low-resource local languages in Indonesia faces significant challenges, including the need for a representative benchmark and limited data avai…
Generating Faithful Text From a Knowledge Graph with Noisy Reference Text
Tahsina Hashem, Weiqing Wang, Derry Tanti Wijaya +2
Knowledge Graph (KG)-to-Text generation aims at generating fluent natural-language text that accurately represents the information of a given knowledge graph. While significant pro…
RL4F: Generating Natural Language Feedback with Reinforcement Learning for Repairing Model Outputs
Afra Feyza Akyürek, Ekin Akyürek, Aman Madaan +4
Despite their unprecedented success, even the largest language models make mistakes. Similar to how humans learn and improve using feedback, previous work proposed providing langua…