5 accepted papers
Agents implemented using Large Language Models (LLMs) offer novel solutions for tasks such as document summarization. However, single-agent systems, limited by their own knowledge base, often exhibit information omissions or inconsistencies with the facts, while multi-agent systems lacking effective
Generating simulation-ready tabletop scenes from task instructions is an intriguing and promising research direction in the field of Embodied AI. However, existing task-to-scene generation methods rely exclusively on large language models (LLMs) to predict scene layouts, inevitably yielding object c…
Designing 3D indoor layouts is a crucial task with significant applications in embodied robot intelligence, virtual reality, and interior design. Existing methods for 3D layout design either rely on diffusion models, which utilize spatial relationship priors, or heavily leverage the inferential capa
Rather than merely to retain previously acquired generalization, achieving synergistic improvements between generalization and domain specialization in foundation models remains a significant challenge in both pre-training and post-training. As an alternative, we propose a test-time cross-domain kno
Automatic indoor layout generation has attracted increasing attention due to its potential in interior design, virtual environment construction, and embodied AI. Existing methods fall into two categories: prompt-driven approaches that leverage proprietary LLM services (e.g., GPT APIs), and learning-…