Large language models (LLMs) have evolved into LLM agents that can use the user conversation context and respond according to the roles of the LLM agents. Recent studies have suggested that LLM-based agents can be used as human-like partners in social interactions. However, the role of the environmental context, particularly spatial information of user space, in the interaction between humans and LLM agents has not been explored. In this study, participants engaged in counselling conversations under three different conditions based on their spatial awareness levels. The dependent measures included copresence, trust, therapist alliances, and self-disclosure. The results suggested that participants in the condition where the LLM actively reflected spatial information generally reported higher levels of user experience. Interestingly, when the LLM actively reflected the spatial context of the user, the participants tended to describe themselves and express their emotions more. These findings suggest that spatially aware LLM agents can contribute to better social interactions between humans and LLM agents. Our findings can be used to design future augmented reality applications in the counselling, education, and healthcare industries.

Abstract We propose a novel, multi‐resolution method to efficiently perform large‐scale cloth simulation. Our cloth simulation method is based on a triangle‐based energy model constructed from a cloth mesh. We identify that solutions of the linear system of cloth simulation are smooth in certain regions of the cloth mesh and solve the linear system on those regions in a reduced solution space. Then we reconstruct the original solutions by performing a simple interpolation from solutions computed in the reduced space. In order to identify regions where solutions are smooth, we propose simplification metrics that consider stretching, shear, and bending forces, as well as geometric collisions. Our multi‐resolution method can be applied to many existing cloth simulation methods, since our method works on a general linear system. In order to demonstrate benefits of our method, we apply our method into four large‐scale cloth benchmarks that consist of tens or hundreds of thousands of triangles. Because of the reduced computations, we achieve a performance improvement by a factor of up to one order of magnitude, with a little loss of simulation quality.

Abstract We present an efficient multigrid algorithm that is adequate to solve a heavy linear system given in cloth simulation. Although a multigrid solver has been successfully employed to the Poisson problems, it is hard to apply the solver to complicated cloth deformations due to its lack of physical meaning in level construction. We address this problem by developing a physically faithful technique ensuring the conservation of all physical quantities across levels. The performance of our approach is demonstrated on a number of garment simulations implemented by the state of the art techniques: the implicit integration, the triangle‐based in‐plane energy model, and the curvature‐based bending energy model. Our multigrid algorithm is about four times faster than the preconditioned Conjugate Gradient method for a garment with 20K particles. Copyright © 2008 John Wiley & Sons, Ltd.

Abstract Simulating a huge number of articulate figures in a real‐time application is one of the challenging research topics in character animation. Several researchers have tried to improve the performance of animation using the image‐based technique such as ‘impostor.’ This method improved the speed of the animation; however, the accuracy, memory, and interactivity problems related to motion remain to be resolved. In this regard, a ‘motion simplification’ framework for an articulate figure is proposed, which not only improves the speed of the animation but also conserves the features of the original motion. First, the motion sequence is analyzed using mean shift clustering for the purpose of extracting key postures and automatically generating the priority of joint reductions. These motion analysis results are directly utilized as the input of the proposed posture optimization. The least square method is applied in order to minimize the error between the original and the simplified posture. Finally, how to apply the proposed simplified motion in a real‐time application without decreasing the visual quality of the scene is shown. The experimental result shows that the proposed motion simplification can be successfully applied in a real‐time animation system. Copyright © 2006 John Wiley & Sons, Ltd.