Search Results for author:
Found 13 papers, 9 papers with code
MoDEM: Mixture of Domain Expert Models
We propose a novel approach to enhancing the performance and efficiency of large language models (LLMs) by combining domain prompt routing with domain-specialized models.
Generating bilingual example sentences with large language models as lexicography assistants
Additionally, we explore the use of pre-trained language models for automated rating of examples, finding that sentence perplexity serves as a good proxy for typicality and intelligibility in higher-resourced languages.
To Aggregate or Not to Aggregate. That is the Question: A Case Study on Annotation Subjectivity in Span Prediction
This paper explores the task of automatic prediction of text spans in a legal problem description that support a legal area label.
NusaX: Multilingual Parallel Sentiment Dataset for 10 Indonesian Local Languages
In this work, we focus on developing resources for languages in Indonesia.
One Country, 700+ Languages: NLP Challenges for Underrepresented Languages and Dialects in Indonesia
NLP research is impeded by a lack of resources and awareness of the challenges presented by underrepresented languages and dialects.
Unsupervised Cross-Lingual Transfer of Structured Predictors without Source Data
Providing technologies to communities or domains where training data is scarce or protected e. g., for privacy reasons, is becoming increasingly important.
PTST-UoM at SemEval-2021 Task 10: Parsimonious Transfer for Sequence Tagging
This paper describes PTST, a source-free unsupervised domain adaptation technique for sequence tagging, and its application to the SemEval-2021 Task 10 on time expression recognition.
PPT: Parsimonious Parser Transfer for Unsupervised Cross-Lingual Adaptation
Cross-lingual transfer is a leading technique for parsing low-resource languages in the absence of explicit supervision.
KaWAT: A Word Analogy Task Dataset for Indonesian
We introduced KaWAT (Kata Word Analogy Task), a new word analogy task dataset for Indonesian.
IndoSum: A New Benchmark Dataset for Indonesian Text Summarization
Automatic text summarization is generally considered as a challenging task in the NLP community.
Toward a Standardized and More Accurate Indonesian Part-of-Speech Tagging
Previous work in Indonesian part-of-speech (POS) tagging are hard to compare as they are not evaluated on a common dataset.
Multi-Task Active Learning for Neural Semantic Role Labeling on Low Resource Conversational Corpus
In this paper, we propose a Multi-Task Active Learning framework for Semantic Role Labeling with Entity Recognition (ER) as the auxiliary task to alleviate the need for extensive data and use additional information from ER to help SRL.
Empirical Evaluation of Character-Based Model on Neural Named-Entity Recognition in Indonesian Conversational Texts
We report an empirical evaluation of neural sequence labeling models with character embedding to tackle NER task in Indonesian conversational texts.
