16 citations · 37 across the 15 of their papers we have counts for
15 papers
Confidently Deceptive: On the Relationship Between Confidence and Deception in LLMs
Ali Asad, Stephen Obadinma, Anshul Pattoo +2
The increasing capabilities of large language models (LLMs) are being accompanied by deep-rooted risks of deceptive behaviours that cause models to produce misleading outputs in se…
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…
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…
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…
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…
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…
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…
SeaLLMs 3: Open Foundation and Chat Multilingual Large Language Models for Southeast Asian Languages
Wenxuan Zhang, Hou Pong Chan, Yiran Zhao +9
Large Language Models (LLMs) have shown remarkable abilities across various tasks, yet their development has predominantly centered on high-resource languages like English and Chin…
Auto-Arena: Automating LLM Evaluations with Agent Peer Battles and Committee Discussions
Ruochen Zhao, Wenxuan Zhang, Yew Ken Chia +3
As LLMs continuously evolve, there is an urgent need for a reliable evaluation method that delivers trustworthy results promptly. Currently, static benchmarks suffer from inflexibi…
Is Translation All You Need? A Study on Solving Multilingual Tasks with Large Language Models
Chaoqun Liu, Wenxuan Zhang, Yiran Zhao +2
Large language models (LLMs) have demonstrated multilingual capabilities, yet they are mostly English-centric due to the imbalanced training corpora. While prior works have leverag…
AdaMergeX: Cross-Lingual Transfer with Large Language Models via Adaptive Adapter Merging
Yiran Zhao, Wenxuan Zhang, Huiming Wang +2
As an effective alternative to the direct fine-tuning on target tasks in specific languages, cross-lingual transfer addresses the challenges of limited training data by decoupling…
How do Large Language Models Handle Multilingualism?
Yiran Zhao, Wenxuan Zhang, Guizhen Chen +2
Large language models (LLMs) have demonstrated impressive capabilities across diverse languages. This study explores how LLMs handle multilingualism. Based on observed language rat…
SeaLLMs -- Large Language Models for Southeast Asia
Xuan-Phi Nguyen, Wenxuan Zhang, Xin Li +14
Despite the remarkable achievements of large language models (LLMs) in various tasks, there remains a linguistic bias that favors high-resource languages, such as English, often at…
SOUL: Towards Sentiment and Opinion Understanding of Language
Yue Deng, Wenxuan Zhang, Sinno Jialin Pan +1
Sentiment analysis is a well-established natural language processing task, with sentiment polarity classification being one of its most popular and representative tasks. However, d…
Multilingual Jailbreak Challenges in Large Language Models
Yue Deng, Wenxuan Zhang, Sinno Jialin Pan +1
While large language models (LLMs) exhibit remarkable capabilities across a wide range of tasks, they pose potential safety concerns, such as the ``jailbreak'' problem, wherein mal…