activity
20212026
most citedNL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation

25 citations · 57 across the 28 of their papers we have counts for

collaborators
Showing cs.CLShow all

24 papers · 1 filter

cs.CL2025

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

Patrick Amadeus Irawan, Ryandito Diandaru, Belati Jagad Bintang Syuhada +5

We introduce Entropy2Vec, a novel framework for deriving cross-lingual language representations by leveraging the entropy of monolingual language models. Unlike traditional typolog…

cs.CL2025

Language Surgery in Multilingual Large Language Models

Joanito Agili Lopo, Muhammad Ravi Shulthan Habibi, Tack Hwa Wong +6

Large Language Models (LLMs) have demonstrated remarkable generalization capabilities across tasks and languages, revolutionizing natural language processing. This paper investigat…

cs.CL2025

What Causes Knowledge Loss in Multilingual Language Models?

Maria Khelli, Samuel Cahyawijaya, Ayu Purwarianti +1

Cross-lingual transfer in natural language processing (NLP) models enhances multilingual performance by leveraging shared linguistic knowledge. However, traditional methods that pr…

cs.CL2025

Command A: An Enterprise-Ready Large Language Model

Team Cohere, :, Aakanksha +227

In this report we describe the development of Command A, a powerful large language model purpose-built to excel at real-world enterprise use cases. Command A is an agent-optimised…

cs.CL2024★ 1 cited

Thank You, Stingray: Multilingual Large Language Models Can Not (Yet) Disambiguate Cross-Lingual Word Sense

Samuel Cahyawijaya, Ruochen Zhang, Holy Lovenia +4

Multilingual large language models (LLMs) have gained prominence, but concerns arise regarding their reliability beyond English. This study addresses the gap in cross-lingual seman…

cs.CL2024★ 2 cited

WorldCuisines: A Massive-Scale Benchmark for Multilingual and Multicultural Visual Question Answering on Global Cuisines

Genta Indra Winata, Frederikus Hudi, Patrick Amadeus Irawan +48

Vision Language Models (VLMs) often struggle with culture-specific knowledge, particularly in languages other than English and in underrepresented cultural contexts. To evaluate th…

cs.CL2024★ 1 cited

LLM for Everyone: Representing the Underrepresented in Large Language Models

Samuel Cahyawijaya

Natural language processing (NLP) has witnessed a profound impact of large language models (LLMs) that excel in a multitude of tasks. However, the limitation of LLMs in multilingua…

cs.CL2024

Towards Efficient and Robust VQA-NLE Data Generation with Large Vision-Language Models

Patrick Amadeus Irawan, Genta Indra Winata, Samuel Cahyawijaya +1

Natural Language Explanation (NLE) aims to elucidate the decision-making process by providing detailed, human-friendly explanations in natural language. It helps demystify the deci…

cs.CL2024★ 2 cited

SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages

Holy Lovenia, Rahmad Mahendra, Salsabil Maulana Akbar +58

Southeast Asia (SEA) is a region rich in linguistic diversity and cultural variety, with over 1,300 indigenous languages and a population of 671 million people. However, prevailing…

cs.CL2023

IndoToD: A Multi-Domain Indonesian Benchmark For End-to-End Task-Oriented Dialogue Systems

Muhammad Dehan Al Kautsar, Rahmah Khoirussyifa' Nurdini, Samuel Cahyawijaya +2

Task-oriented dialogue (ToD) systems have been mostly created for high-resource languages, such as English and Chinese. However, there is a need to develop ToD systems for other re…

cs.CL2023★ 1 cited

InstructTODS: Large Language Models for End-to-End Task-Oriented Dialogue Systems

Willy Chung, Samuel Cahyawijaya, Bryan Wilie +2

Large language models (LLMs) have been used for diverse tasks in natural language processing (NLP), yet remain under-explored for task-oriented dialogue systems (TODS), especially…

cs.CL2023

PICK: Polished & Informed Candidate Scoring for Knowledge-Grounded Dialogue Systems

Bryan Wilie, Yan Xu, Willy Chung +3

Grounding dialogue response generation on external knowledge is proposed to produce informative and engaging responses. However, current knowledge-grounded dialogue (KGD) systems o…

cs.CL2023

Cross-Lingual Cross-Age Group Adaptation for Low-Resource Elderly Speech Emotion Recognition

Samuel Cahyawijaya, Holy Lovenia, Willy Chung +3

Speech emotion recognition plays a crucial role in human-computer interactions. However, most speech emotion recognition research is biased toward English-speaking adults, which hi…

cs.CL2023★ 1 cited

Multi-lingual and Multi-cultural Figurative Language Understanding

Anubha Kabra, Emmy Liu, Simran Khanuja +6

Figurative language permeates human communication, but at the same time is relatively understudied in NLP. Datasets have been created in English to accelerate progress towards meas…

cs.CL2023★ 6 cited

Prompting Multilingual Large Language Models to Generate Code-Mixed Texts: The Case of South East Asian Languages

Zheng-Xin Yong, Ruochen Zhang, Jessica Zosa Forde +12

While code-mixing is a common linguistic practice in many parts of the world, collecting high-quality and low-cost code-mixed data remains a challenge for natural language processi…

cs.CL2022★ 2 cited

Every picture tells a story: Image-grounded controllable stylistic story generation

Holy Lovenia, Bryan Wilie, Romain Barraud +3

Generating a short story out of an image is arduous. Unlike image captioning, story generation from an image poses multiple challenges: preserving the story coherence, appropriatel…

cs.CL2022★ 3 cited

GEMv2: Multilingual NLG Benchmarking in a Single Line of Code

Sebastian Gehrmann, Abhik Bhattacharjee, Abinaya Mahendiran +74

Evaluation in machine learning is usually informed by past choices, for example which datasets or metrics to use. This standardization enables the comparison on equal footing using…

cs.CL2022★ 7 cited

Towards Answering Open-ended Ethical Quandary Questions

Yejin Bang, Nayeon Lee, Tiezheng Yu +10

Considerable advancements have been made in various NLP tasks based on the impressive power of large language models (LLMs) and many NLP applications are deployed in our daily live…

cs.CL2022

Can Question Rewriting Help Conversational Question Answering?

Etsuko Ishii, Yan Xu, Samuel Cahyawijaya +1

Question rewriting (QR) is a subtask of conversational question answering (CQA) aiming to ease the challenges of understanding dependencies among dialogue history by reformulating…

cs.CL2022

Clozer: Adaptable Data Augmentation for Cloze-style Reading Comprehension

Holy Lovenia, Bryan Wilie, Willy Chung +4

Task-adaptive pre-training (TAPT) alleviates the lack of labelled data and provides performance lift by adapting unlabelled data to downstream task. Unfortunately, existing adaptat…

cs.CL2022★ 2 cited

VScript: Controllable Script Generation with Visual Presentation

Ziwei Ji, Yan Xu, I-Tsun Cheng +6

In order to offer a customized script tool and inspire professional scriptwriters, we present VScript. It is a controllable pipeline that generates complete scripts, including dial…

cs.CL2021

ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversation

Holy Lovenia, Samuel Cahyawijaya, Genta Indra Winata +11

Code-switching is a speech phenomenon occurring when a speaker switches language during a conversation. Despite the spontaneous nature of code-switching in conversational spoken la…

cs.CL2021★ 25 cited

NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation

Kaustubh D. Dhole, Varun Gangal, Sebastian Gehrmann +122

Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained…

cs.CL2021

ERICA: An Empathetic Android Companion for Covid-19 Quarantine

Etsuko Ishii, Genta Indra Winata, Samuel Cahyawijaya +3

Over the past year, research in various domains, including Natural Language Processing (NLP), has been accelerated to fight against the COVID-19 pandemic, yet such research has jus…