13 citations · 27 across the 7 of their papers we have counts for
7 papers
Mind Meets Space: Rethinking Agentic Spatial Intelligence from a Neuroscience-inspired Perspective
Bui Duc Manh, Soumyaratna Debnath, Zetong Zhang +6
Recent advances in agentic AI have led to systems capable of autonomous task execution and language-based reasoning, yet their spatial reasoning abilities remain limited and undere…
SEA-BED: How Do Embedding Models Represent Southeast Asian Languages?
Wuttikorn Ponwitayarat, Peerat Limkonchotiwat, Raymond Ng +9
Multilingual text embeddings are often assumed to encode meaning in a perspective-independent semantic space, yielding stable similarity judgments across tasks and languages. Our r…
Neural Brain: A Neuroscience-inspired Framework for Embodied Agents
Jian Liu, Xiongtao Shi, Thai Duy Nguyen +13
The rapid evolution of artificial intelligence (AI) has shifted from static, data-driven models to dynamic systems capable of perceiving and interacting with real-world environment…
SEA-LION: Southeast Asian Languages in One Network
Raymond Ng, Thanh Ngan Nguyen, Yuli Huang +28
Recently, Large Language Models (LLMs) have dominated much of the artificial intelligence scene with their ability to process and generate natural languages. However, the majority…
When Words Smile: Generating Diverse Emotional Facial Expressions from Text
Haidong Xu, Meishan Zhang, Hao Ju +4
Enabling digital humans to express rich emotions has significant applications in dialogue systems, gaming, and other interactive scenarios. While recent advances in talking head sy…
XAI meets LLMs: A Survey of the Relation between Explainable AI and Large Language Models
Erik Cambria, Lorenzo Malandri, Fabio Mercorio +2
In this survey, we address the key challenges in Large Language Models (LLM) research, focusing on the importance of interpretability. Driven by increasing interest from AI and bus…
Rethinking Large Language Models in Mental Health Applications
Shaoxiong Ji, Tianlin Zhang, Kailai Yang +2
Large Language Models (LLMs) have become valuable assets in mental health, showing promise in both classification tasks and counseling applications. This paper offers a perspective…