565 citations · 1.3k across the 96 of their papers we have counts for
17 papers · 1 filter
Maya: An Instruction Finetuned Multilingual Multimodal Model
Nahid Alam, Karthik Reddy Kanjula, Surya Guthikonda +16
The rapid development of large Vision-Language Models (VLMs) has led to impressive results on academic benchmarks, primarily in widely spoken languages. However, significant gaps r…
A Multi-Agent Dual Dialogue System to Support Mental Health Care Providers
Onno P. Kampman, Ye Sheng Phang, Stanley Han +9
We introduce a general-purpose, human-in-the-loop dual dialogue system to support mental health care professionals. The system, co-designed with care providers, is conceptualized t…
MetaMetrics-MT: Tuning Meta-Metrics for Machine Translation via Human Preference Calibration
David Anugraha, Garry Kuwanto, Lucky Susanto +2
We present MetaMetrics-MT, an innovative metric designed to evaluate machine translation (MT) tasks by aligning closely with human preferences through Bayesian optimization with Ga…
Linguistics Theory Meets LLM: Code-Switched Text Generation via Equivalence Constrained Large Language Models
Garry Kuwanto, Chaitanya Agarwal, Genta Indra Winata +1
Code-switching, the phenomenon of alternating between two or more languages in a single conversation, presents unique challenges for Natural Language Processing (NLP). Most existin…
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…
RainbowPO: A Unified Framework for Combining Improvements in Preference Optimization
Hanyang Zhao, Genta Indra Winata, Anirban Das +4
Recently, numerous preference optimization algorithms have been introduced as extensions to the Direct Preference Optimization (DPO) family. While these methods have successfully a…
MetaMetrics: Calibrating Metrics For Generation Tasks Using Human Preferences
Genta Indra Winata, David Anugraha, Lucky Susanto +2
Understanding the quality of a performance evaluation metric is crucial for ensuring that model outputs align with human preferences. However, it remains unclear how well each metr…
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…
Preference Tuning with Human Feedback on Language, Speech, and Vision Tasks: A Survey
Genta Indra Winata, Hanyang Zhao, Anirban Das +4
Preference tuning is a crucial process for aligning deep generative models with human preferences. This survey offers a thorough overview of recent advancements in preference tunin…
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…
ProxyLM: Predicting Language Model Performance on Multilingual Tasks via Proxy Models
David Anugraha, Genta Indra Winata, Chenyue Li +2
Performance prediction is a method to estimate the performance of Language Models (LMs) on various Natural Language Processing (NLP) tasks, mitigating computational costs associate…
MINERS: Multilingual Language Models as Semantic Retrievers
Genta Indra Winata, Ruochen Zhang, David Ifeoluwa Adelani
Words have been represented in a high-dimensional vector space that encodes their semantic similarities, enabling downstream applications such as retrieving synonyms, antonyms, and…
Lessons from the Trenches on Reproducible Evaluation of Language Models
Stella Biderman, Hailey Schoelkopf, Lintang Sutawika +27
Reliable evaluation of language models (LMs) remains an open challenge. Re- searchers and engineers face methodological issues such as the sensitivity of models to evaluation setup…
Synthetic Data Generation and Joint Learning for Robust Code-Mixed Translation
Kartik Kartik, Sanjana Soni, Anoop Kunchukuttan +2
The widespread online communication in a modern multilingual world has provided opportunities to blend more than one language (aka code-mixed language) in a single utterance. This…
Cendol: Open Instruction-tuned Generative Large Language Models for Indonesian Languages
Samuel Cahyawijaya, Holy Lovenia, Fajri Koto +13
Large language models (LLMs) show remarkable human-like capability in various domains and languages. However, a notable quality gap arises in low-resource languages, e.g., Indonesi…
SemRel2024: A Collection of Semantic Textual Relatedness Datasets for 13 Languages
Nedjma Ousidhoum, Shamsuddeen Hassan Muhammad, Mohamed Abdalla +24
Exploring and quantifying semantic relatedness is central to representing language and holds significant implications across various NLP tasks. While earlier NLP research primarily…
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…