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Chain-of-Thought (CoT) prompting has proven highly effective for enhancing complex reasoning in Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs). Yet, it struggles in complex spatial reasoning tasks. Nonetheless,…
Multimodal Large Language Models (MLLMs) show promising results for embodied agents in operating meaningfully in complex, human-centered environments. Yet, evaluating their capacity for nuanced, human-like reasoning and decision-making…
We have been developing a visualization application for CAVE-type virtual reality (VR) systems for more than a decade. This application, VFIVE, is currently used in several CAVE systems in Japan for routine visualizations. It is also used…
Identification within media, whether with real or fictional characters, significantly impacts users, shaping their behavior and enriching their social and emotional experiences. Immersive media, like video games, utilize virtual entities…
The rapidly developing Large Vision Language Models (LVLMs) have shown notable capabilities on a range of multi-modal tasks, but still face the hallucination phenomena where the generated texts do not align with the given contexts,…
Artificial Intelligence (AI), especially Neural Networks (NNs), has become increasingly popular. However, people usually treat AI as a tool, focusing on improving outcome, accuracy, and performance while paying less attention to the…
Visual navigation is a fundamental capability for autonomous home-assistance robots, enabling long-horizon tasks such as object search. While recent methods have leveraged Large Language Models (LLMs) to incorporate commonsense reasoning…
Vision language models (VLMs) are AI systems paired with both language and vision encoders to process multimodal input. They are capable of performing complex semantic tasks such as automatic captioning, but it remains an open question…
Recent advancements in Vision-Language (VL) research have sparked new benchmarks for complex visual reasoning, challenging models' advanced reasoning ability. Traditional Vision-Language Models (VLMs) perform well in visual perception tasks…
One of the emergent challenges of student work submitted for assessment is the widespread use of large language models (LLMs) to support and even produce written work. This particularly affects subjects where long-form written work is a key…
The CAVE-type virtual reality (VR) system was introduced for scientific visualization of large scale data in the plasma simulation community about a decade ago. Since then, we have been developing a VR visualization software, VFIVE, for…
Reinforcement Learning Finetuning (RFT) has significantly advanced the reasoning capabilities of large language models (LLMs) by enabling long chains of thought, self-correction, and effective tool use. While recent works attempt to extend…
This study will investigate the user experience while interacting with highly photorealistic virtual job interviewer avatars in Virtual Reality (VR), Augmented Reality (AR), and on a 2D screen. Having a precise speech recognition mechanism,…
Virtual Reality (VR) provides immersive experiences in the virtual world, but it may reduce users' awareness of physical surroundings and cause safety concerns and psychological discomfort. Hence, there is a need of an ambient information…
Immersive technologies are capable of transporting people to distant or inaccessible environments that they might not otherwise visit. Practitioners and researchers alike are discovering new ways to replicate and enhance existing tourism…
We present VOICE, a novel approach to science communication that connects large language models' (LLM) conversational capabilities with interactive exploratory visualization. VOICE introduces several innovative technical contributions that…
Human cognition significantly influences expressed behavior and is intrinsically tied to authentic personality traits. Personality assessment plays a pivotal role in various fields, including psychology, education, social media, etc.…
Recent advances in Vision-Language Models (VLMs) have benefited from Reinforcement Learning (RL) for enhanced reasoning. However, existing methods still face critical limitations, including the lack of low-level visual information and…
User engagement is greatly enhanced by fully immersive multi-modal experiences that combine visual and auditory stimuli. Consequently, the next frontier in VR/AR technologies lies in immersive volumetric videos with complete scene capture,…
Traditional neural network models for intent inference rely heavily on observable states and struggle to generalize across diverse tasks and dynamic environments. Recent advances in Vision Language Models (VLMs) and Vision Language Action…