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This paper introduces DART-LLM, a novel framework that employs Directed Acyclic Graphs (DAGs) to model task dependencies, enabling the decomposition of natural language instructions into well-coordinated subtasks for multi-robot execution. DART-LLM comprises four key components: a Question-Answering (QA) LLM module for dependency-aware task decomposition, a Breakdown Function module for robot assignment, an Actuation module for execution, and a Vision-Language Model (VLM)-based object detector for environmental perception, achieving end-to-end task execution. Experimental results across three task complexity levels demonstrate that DART-LLM achieves state-of-the-art performance, significantly outperforming the baseline across all evaluation metrics. Among the tested models, DeepSeek-r1-671B achieves the highest success rate, whereas Llama-3.1-8B exhibits superior response time reliability. Ablation studies further confirm that explicit dependency modeling notably enhances the performance of smaller models, facilitating efficient deployment on resource-constrained platforms. Please refer to the project website https://wyd0817.github.io/project-dart-llm/ for videos and code.","url_abs":"https://arxiv.org/abs/2411.09022v2","url_pdf":"https://arxiv.org/pdf/2411.09022v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"dart-llm-dependency-aware-multi-robot-task","repo_url":"https://github.com/wyd0817/Breakdown_Function_Modules","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"dart-llm-dependency-aware-multi-robot-task","repo_url":"https://github.com/wyd0817/Actuation_Module","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"dart-llm-dependency-aware-multi-robot-task","repo_url":"https://github.com/wyd0817/DART_LLM_Docker","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"dart-llm-dependency-aware-multi-robot-task","repo_url":"https://github.com/wyd0817/DART_LLM_Sim","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok","spdx":"Apache-2.0"}},{"paper_slug":"dart-llm-dependency-aware-multi-robot-task","repo_url":"https://github.com/wyd0817/QA_LLM_Module","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"dart-llm-dependency-aware-multi-robot-task","repo_url":"https://github.com/wyd0817/Sensor_Module","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2411.09022","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2411.09022"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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