activity
20242026
collaborators

6 papers

cs.CL2025

SeaLLMs-Audio: Large Audio-Language Models for Southeast Asia

Chaoqun Liu, Mahani Aljunied, Guizhen Chen +4

We introduce SeaLLMs-Audio, the first large audio-language model (LALM) tailored for multiple Southeast Asian (SEA) languages-Indonesian (id), Thai (th), and Vietnamese (vi)-alongs…

cs.CL2025

Reframe Your Life Story: Interactive Narrative Therapist and Innovative Moment Assessment with Large Language Models

Yi Feng, Jiaqi Wang, Wenxuan Zhang +6

Recent progress in large language models (LLMs) has opened new possibilities for mental health support, yet current approaches lack realism in simulating specialized psychotherapy…

cs.CL2025

Pruning General Large Language Models into Customized Expert Models

Yirao Zhao, Guizhen Chen, Kenji Kawaguchi +2

Large language models (LLMs) have revolutionized natural language processing, yet their substantial model sizes often require substantial computational resources. To preserve compu…

cs.CL2025

Babel: Open Multilingual Large Language Models Serving Over 90% of Global Speakers

Yiran Zhao, Chaoqun Liu, Yue Deng +8

Large language models (LLMs) have revolutionized natural language processing (NLP), yet open-source multilingual LLMs remain scarce, with existing models often limited in language…

cs.CL2025

SeaExam and SeaBench: Benchmarking LLMs with Local Multilingual Questions in Southeast Asia

Chaoqun Liu, Wenxuan Zhang, Jiahao Ying +3

This study introduces two novel benchmarks, SeaExam and SeaBench, designed to evaluate the capabilities of Large Language Models (LLMs) in Southeast Asian (SEA) application scenari…

cs.CL2024

Zero-to-Strong Generalization: Eliciting Strong Capabilities of Large Language Models Iteratively without Gold Labels

Chaoqun Liu, Qin Chao, Wenxuan Zhang +4

Large Language Models (LLMs) have demonstrated remarkable performance through supervised fine-tuning or in-context learning using gold labels. However, this paradigm is limited by…