9 citations · 26 across the 15 of their papers we have counts for
16 papers
Datasheets Aren't Enough: DataRubrics for Automated Quality Metrics and Accountability
Genta Indra Winata, David Anugraha, Emmy Liu +17
High-quality datasets are fundamental to training and evaluating machine learning models, yet their creation-especially with accurate human annotations-remains a significant challe…
Crosslingual Reasoning through Test-Time Scaling
Zheng-Xin Yong, M. Farid Adilazuarda, Jonibek Mansurov +7
Reasoning capabilities of large language models are primarily studied for English, even when pretrained models are multilingual. In this work, we investigate to what extent English…
From Surveys to Narratives: Rethinking Cultural Value Adaptation in LLMs
Muhammad Farid Adilazuarda, Chen Cecilia Liu, Iryna Gurevych +1
Adapting cultural values in Large Language Models (LLMs) presents significant challenges, particularly due to biases and limited training data. Prior work primarily aligns LLMs wit…
NusaAksara: A Multimodal and Multilingual Benchmark for Preserving Indonesian Indigenous Scripts
Muhammad Farid Adilazuarda, Musa Izzanardi Wijanarko, Lucky Susanto +3
Indonesia is rich in languages and scripts. However, most NLP progress has been made using romanized text. In this paper, we present NusaAksara, a novel public benchmark for Indone…
QLESS: A Quantized Approach for Data Valuation and Selection in Large Language Model Fine-Tuning
Moses Ananta, Muhammad Farid Adilazuarda, Zayd Muhammad Kawakibi Zuhri +2
Fine-tuning large language models (LLMs) is often constrained by the computational costs of processing massive datasets. We propose \textbf{QLESS} (Quantized Low-rank Gradient Simi…
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…
Cultural Conditioning or Placebo? On the Effectiveness of Socio-Demographic Prompting
Sagnik Mukherjee, Muhammad Farid Adilazuarda, Sunayana Sitaram +3
Socio-demographic prompting is a commonly employed approach to study cultural biases in LLMs as well as for aligning models to certain cultures. In this paper, we systematically pr…
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…
MLKV: Multi-Layer Key-Value Heads for Memory Efficient Transformer Decoding
Zayd Muhammad Kawakibi Zuhri, Muhammad Farid Adilazuarda, Ayu Purwarianti +1
Auto-regressive inference of transformers benefit greatly from Key-Value (KV) caching, but can lead to major memory bottlenecks as model size, batch size, and sequence length grow…
CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark
David Romero, Chenyang Lyu, Haryo Akbarianto Wibowo +73
Visual Question Answering (VQA) is an important task in multimodal AI, and it is often used to test the ability of vision-language models to understand and reason on knowledge pres…
Towards Measuring and Modeling "Culture" in LLMs: A Survey
Muhammad Farid Adilazuarda, Sagnik Mukherjee, Pradhyumna Lavania +5
We present a survey of more than 90 recent papers that aim to study cultural representation and inclusion in large language models (LLMs). We observe that none of the studies expli…
LinguAlchemy: Fusing Typological and Geographical Elements for Unseen Language Generalization
Muhammad Farid Adilazuarda, Samuel Cahyawijaya, Alham Fikri Aji +2
Pretrained language models (PLMs) have become remarkably adept at task and language generalization. Nonetheless, they often fail when faced with unseen languages. In this work, we…
IndoRobusta: Towards Robustness Against Diverse Code-Mixed Indonesian Local Languages
Muhammad Farid Adilazuarda, Samuel Cahyawijaya, Genta Indra Winata +2
Significant progress has been made on Indonesian NLP. Nevertheless, exploration of the code-mixing phenomenon in Indonesian is limited, despite many languages being frequently mixe…
The Obscure Limitation of Modular Multilingual Language Models
Muhammad Farid Adilazuarda, Samuel Cahyawijaya, Ayu Purwarianti
We expose the limitation of modular multilingual language models (MLMs) in multilingual inference scenarios with unknown languages. Existing evaluations of modular MLMs exclude the…
Beyond Turing: A Comparative Analysis of Approaches for Detecting Machine-Generated Text
Muhammad Farid Adilazuarda
Significant progress has been made on text generation by pre-trained language models (PLMs), yet distinguishing between human and machine-generated text poses an escalating challen…
NusaCrowd: Open Source Initiative for Indonesian NLP Resources
Samuel Cahyawijaya, Holy Lovenia, Alham Fikri Aji +44
We present NusaCrowd, a collaborative initiative to collect and unify existing resources for Indonesian languages, including opening access to previously non-public resources. Thro…