Samuel Cahyawijaya

NL-Augmenter 🦎 → 🐍 A Framework for Task-Sensitive Natural Language Augmentation

2023 · Northern European Journal of Language Technology

Data augmentation is an important method for evaluating the robustness of and enhancing the diversity of training data for natural language processing (NLP) models. In this paper, we present NL-Augmenter, a new participatory Python-based natural …

One Country, 700+ Languages: NLP Challenges for Underrepresented Languages and Dialects in Indonesia

2022 · arXiv (Cornell University)

NLP research is impeded by a lack of resources and awareness of the challenges presented by underrepresented languages and dialects. Focusing on the languages spoken in Indonesia, the second most linguistically diverse and the fourth …

NusaCrowd: Open Source Initiative for Indonesian NLP Resources

2022 · arXiv (Cornell University)

We present NusaCrowd, a collaborative initiative to collect and unify existing resources for Indonesian languages, including opening access to previously non-public resources. Through this initiative, we have brought together 137 datasets and 118 standardized data …

Which One Are You Referring To? Multimodal Object Identification in Situated Dialogue

2023 · arXiv (Cornell University)

The demand for multimodal dialogue systems has been rising in various domains, emphasizing the importance of interpreting multimodal inputs from conversational and situational contexts. We explore three methods to tackle this problem and evaluate them …

Entropy2Vec: Crosslingual Language Modeling Entropy as End-to-End Learnable Language Representations

2025 · arXiv (Cornell University)

We introduce Entropy2Vec, a novel framework for deriving cross-lingual language representations by leveraging the entropy of monolingual language models. Unlike traditional typological inventories that suffer from feature sparsity and static snapshots, Entropy2Vec uses the inherent …

A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity

2023 · arXiv (Cornell University)

This paper proposes a framework for quantitatively evaluating interactive LLMs such as ChatGPT using publicly available data sets. We carry out an extensive technical evaluation of ChatGPT using 23 data sets covering 8 different common …