13 citations · 27 across the 7 of their papers we have counts for
4 papers · 1 filter
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…
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…
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…