10 citations · 22 across the 6 of their papers we have counts for
6 papers
GLM-5V-Turbo: Toward a Native Foundation Model for Multimodal Agents
V Team, Wenyi Hong, Xiaotao Gu +94
We present GLM-5V-Turbo, a step toward native foundation models for multimodal agents. As foundation models are increasingly deployed in real environments, agentic capability depen…
PFML-based Semantic BCI Agent for Game of Go Learning and Prediction
Chang-Shing Lee, Mei-Hui Wang, Li-Wei Ko +8
This paper presents a semantic brain computer interface (BCI) agent with particle swarm optimization (PSO) based on a Fuzzy Markup Language (FML) for Go learning and prediction app…
Ontology-based Fuzzy Markup Language Agent for Student and Robot Co-Learning
Chang-Shing Lee, Mei-Hui Wang, Tzong-Xiang Huang +6
An intelligent robot agent based on domain ontology, machine learning mechanism, and Fuzzy Markup Language (FML) for students and robot co-learning is presented in this paper. The…
Ontology-based Adaptive e-Textbook Platform for Student and Machine Co-Learning
Noel Nuo Wi Tay, Sheng-Chi Yang, Chang-Shing Lee +1
The use of electronic textbooks (e-book) has been heavily studied over the years due to their flexibility, accessibility, interactivity and extensibility. Yet current shortcomings…
FML-based Dynamic Assessment Agent for Human-Machine Cooperative System on Game of Go
Chang-Shing Lee, Mei-Hui Wang, Sheng-Chi Yang +7
In this paper, we demonstrate the application of Fuzzy Markup Language (FML) to construct an FML-based Dynamic Assessment Agent (FDAA), and we present an FML-based Human-Machine Co…
FML-based Prediction Agent and Its Application to Game of Go
Chang-Shing Lee, Mei-Hui Wang, Chia-Hsiu Kao +5
In this paper, we present a robotic prediction agent including a darkforest Go engine, a fuzzy markup language (FML) assessment engine, an FML-based decision support engine, and a…