8 papers
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…
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…
Global PIQA: Evaluating Commonsense Reasoning Across 100+ Languages and Cultures
Tyler A. Chang, Catherine Arnett, Abdelrahman Sadallah +377
To date, there exist almost no culturally-specific evaluation benchmarks for large language models (LLMs) that cover a large number of languages and cultures. In this paper, we pre…
Exploring Cross-Client Memorization of Training Data in Large Language Models for Federated Learning
Tinnakit Udsa, Can Udomcharoenchaikit, Patomporn Payoungkhamdee +2
Federated learning (FL) enables collaborative training without raw data sharing, but still risks training data memorization. Existing FL memorization detection techniques focus on…
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…
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…