collaborators

8 papers

cs.CL2026

VIVID: A Culturally Grounded Benchmark Exposing the Figurative Language Gap in Vietnamese NLP

Tu Tran Do, Nhat Ngoc Nguyen, Khanh-Tung Tran +3

We present VIVID (Vietnamese Idioms for Validation and Interpretation Depth), the first systematic benchmark for evaluating culturally grounded figurative language understanding in…

cs.CL2025

Reasoning Transfer for an Extremely Low-Resource and Endangered Language: Bridging Languages Through Sample-Efficient Language Understanding

Khanh-Tung Tran, Barry O'Sullivan, Hoang D. Nguyen

Recent advances have enabled Large Language Models (LLMs) to tackle reasoning tasks by generating chain-of-thought (CoT) rationales, yet these gains have largely applied to high-re…

cs.AI2025

Questionnaire meets LLM: A Benchmark and Empirical Study of Structural Skills for Understanding Questions and Responses

Duc-Hai Nguyen, Vijayakumar Nanjappan, Barry O'Sullivan +1

Millions of people take surveys every day, from market polls and academic studies to medical questionnaires and customer feedback forms. These datasets capture valuable insights, b…

cs.CL2025

Irish-BLiMP: A Linguistic Benchmark for Evaluating Human and Language Model Performance in a Low-Resource Setting

Josh McGiff, Khanh-Tung Tran, William Mulcahy +7

We present Irish-BLiMP (Irish Benchmark of Linguistic Minimal Pairs), the first dataset and framework designed for fine-grained evaluation of linguistic competence in the Irish lan…

cs.LG2025

OWLViz: An Open-World Benchmark for Visual Question Answering

Thuy Nguyen, Dang Nguyen, Hoang Nguyen +3

We present a challenging benchmark for the Open WorLd VISual question answering (OWLViz) task. OWLViz presents concise, unambiguous queries that require integrating multiple capabi…

cs.CL2025

IRLBench: A Multi-modal, Culturally Grounded, Parallel Irish-English Benchmark for Open-Ended LLM Reasoning Evaluation

Khanh-Tung Tran, Barry O'Sullivan, Hoang D. Nguyen

Recent advances in Large Language Models (LLMs) have demonstrated promising knowledge and reasoning abilities, yet their performance in multilingual and low-resource settings remai…