collaborators

6 papers

cs.CL2026

SEATauBench: Adapting Tool-Agent-User Evaluation Into Low-Resource Southeast Asian Languages

My Chiffon Nguyen, Aulia Adila, Saksorn Ruangtanusak +4

While AI development and evaluation for Southeast Asia (SEA) has grown rapidly, agent capabilities in regional languages are still poorly understood despite its importance to sover…

cs.CL2026

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…

cs.CL2026

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.…

cs.LG2026

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…

cs.CL2025

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…

cs.CL2025

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…