80 citations · 96 across the 34 of their papers we have counts for
31 papers · 1 filter
Zero-shot Dependency Parsing with Unsupervised Cross-Lingual Bootstrapping
Lalita Lowphansirikul, Attapol Rutherford, Jian Gang Ngui +2
Pre-trained language models (PLMs) with encoder-based architectures have shown impressive capabilities in zero-shot cross-lingual transfer for various language understanding tasks.…
SEA-CLIP-Tiny: Efficient Multilingual Text-Vision Embedding for Southeast Asian Languages
Puja Ahmad Habibi, Faiz Assabil Firdaus, Ashvanth S +3
Multilingual text-vision embedding models are essential for cross-lingual image-text retrieval, but Southeast Asian languages remain poorly supported due to the region's linguistic…
Exploring Extrinsic and Intrinsic Properties for Effective Reasoning with Code Interpreter
Patomporn Payoungkhamdee, Napat Laosaengpha, Jenta Wonglertsakul +8
Reasoning with a Code Interpreter (CI) has emerged as an effective paradigm for enhancing the reasoning capabilities of large language models (LLMs) through executable computation…
DuDi: Dual-Signal Distillation with Cross-Lingual Verbalizer
Patomporn Payoungkhamdee, Tinnakit Udsa, Jian Gang Ngui +3
Small language models (SLMs) are efficient and scalable, but their multilingual capabilities degrade severely at sub-billion scales, especially for Southeast Asian (SEA) languages.…
SEA-NLI: Natural Language Inference as a Lens into Southeast Asian Cultural Understanding
Peerawat Chomphooyod, Jian Gang Ngui, Yosephine Susanto +5
Frontier LLMs perform well in Western contexts, but remain poorly tested on underrepresented cultures such as those in Southeast Asia (SEA). Existing NLI benchmarks are largely Wes…
SEA-LION-Embedding: Open and Reproducible Text Embeddings for Southeast Asia
Peerat Limkonchotiwat, Raymond Ng, Sarana Nutanong +1
Text embeddings are fundamental to many downstream applications, making robustness important for real-world NLP. However, most recent state-of-the-art embedding models are not repr…
SEA-Guard: Culturally Grounded Multilingual Safeguard for Southeast Asia
Panuthep Tasawong, Jian Gang Ngui, Alham Fikri Aji +2
Culturally aware safeguards are crucial for AI alignment in real-world settings, where safety extends beyond common sense and encompasses diverse local values, norms, and region-sp…
BURMESE-SAN: Burmese NLP Benchmark for Evaluating Large Language Models
Thura Aung, Jann Railey Montalan, Jian Gang Ngui +1
We introduce BURMESE-SAN, the first holistic benchmark that systematically evaluates large language models (LLMs) for Burmese across three core NLP competencies: understanding (NLU…
MultiLexNorm++: A Unified Benchmark and a Generative Model for Lexical Normalization for Asian Languages
Weerayut Buaphet, Thanh-Nhi Nguyen, Risa Kondo +8
Social media data has been of interest to Natural Language Processing (NLP) practitioners for over a decade, because of its richness in information, but also challenges for automat…
SEA-SafeguardBench: Evaluating AI Safety in SEA Languages and Cultures
Panuthep Tasawong, Jian Gang Ngui, Alham Fikri Aji +2
Safeguard models help large language models (LLMs) detect and block harmful content, but most evaluations remain English-centric and overlook linguistic and cultural diversity. Exi…
Distilling Multilingual Vision-Language Models: When Smaller Models Stay Multilingual
Sukrit Sriratanawilai, Jhayahgrit Thongwat, Romrawin Chumpu +3
Vision-language models (VLMs) exhibit uneven performance across languages, a problem that is often exacerbated when the model size is reduced. While Knowledge distillation (KD) dem…
WangchanThaiInstruct: An instruction-following Dataset for Culture-Aware, Multitask, and Multi-domain Evaluation in Thai
Peerat Limkonchotiwat, Pume Tuchinda, Lalita Lowphansirikul +5
Large language models excel at instruction-following in English, but their performance in low-resource languages like Thai remains underexplored. Existing benchmarks often rely on…
SEADialogues: A Multilingual Culturally Grounded Multi-turn Dialogue Dataset on Southeast Asian Languages
Muhammad Dehan Al Kautsar, Aswin Candra, Muhammad Alif Al Hakim +6
Although numerous datasets have been developed to support dialogue systems, most existing chit-chat datasets overlook the cultural nuances inherent in natural human conversations.…
SEA-BED: How Do Embedding Models Represent Southeast Asian Languages?
Wuttikorn Ponwitayarat, Peerat Limkonchotiwat, Raymond Ng +9
Multilingual text embeddings are often assumed to encode meaning in a perspective-independent semantic space, yielding stable similarity judgments across tasks and languages. Our r…
Mangosteen: An Open Thai Corpus for Language Model Pretraining
Wannaphong Phatthiyaphaibun, Can Udomcharoenchaikit, Pakpoom Singkorapoom +4
Pre-training data shapes a language model's quality, but raw web text is noisy and demands careful cleaning. Existing large-scale corpora rely on English-centric or language-agnost…
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…
Assessing Thai Dialect Performance in LLMs with Automatic Benchmarks and Human Evaluation
Peerat Limkonchotiwat, Kanruethai Masuk, Surapon Nonesung +4
Large language models show promising results in various NLP tasks. Despite these successes, the robustness and consistency of LLMs in underrepresented languages remain largely unex…
SEA-LION: Southeast Asian Languages in One Network
Raymond Ng, Thanh Ngan Nguyen, Yuli Huang +28
Recently, Large Language Models (LLMs) have dominated much of the artificial intelligence scene with their ability to process and generate natural languages. However, the majority…
Towards Better Understanding of Program-of-Thought Reasoning in Cross-Lingual and Multilingual Environments
Patomporn Payoungkhamdee, Pume Tuchinda, Jinheon Baek +6
Multi-step reasoning is essential for large language models (LLMs), yet multilingual performance remains challenging. While Chain-of-Thought (CoT) prompting improves reasoning, it…
SEA-HELM: Southeast Asian Holistic Evaluation of Language Models
Yosephine Susanto, Adithya Venkatadri Hulagadri, Jann Railey Montalan +7
With the rapid emergence of novel capabilities in Large Language Models (LLMs), the need for rigorous multilingual and multicultural benchmarks that are integrated has become more…
Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation
Shivalika Singh, Angelika Romanou, Clémentine Fourrier +21
Cultural biases in multilingual datasets pose significant challenges for their effectiveness as global benchmarks. These biases stem not only from differences in language but also…
Seed-Free Synthetic Data Generation Framework for Instruction-Tuning LLMs: A Case Study in Thai
Parinthapat Pengpun, Can Udomcharoenchaikit, Weerayut Buaphet +1
We present a synthetic data approach for instruction-tuning large language models (LLMs) for low-resource languages in a data-efficient manner, specifically focusing on Thai. We id…
Can General-Purpose Large Language Models Generalize to English-Thai Machine Translation ?
Jirat Chiaranaipanich, Naiyarat Hanmatheekuna, Jitkapat Sawatphol +6
Large language models (LLMs) perform well on common tasks but struggle with generalization in low-resource and low-computation settings. We examine this limitation by testing vario…
On Creating an English-Thai Code-switched Machine Translation in Medical Domain
Parinthapat Pengpun, Krittamate Tiankanon, Amrest Chinkamol +11
Machine translation (MT) in the medical domain plays a pivotal role in enhancing healthcare quality and disseminating medical knowledge. Despite advancements in English-Thai MT tec…