SituationalLLM: Proactive language models with scene awareness for dynamic, contextual task guidance

• URL: http://arxiv.org/abs/2406.13302v3
• Date: Fri, 31 Jan 2025 12:35:54 GMT
• Title: SituationalLLM: Proactive language models with scene awareness for dynamic, contextual task guidance
• Authors: Muhammad Saif Ullah Khan, Muhammad Zeshan Afzal, Didier Stricker,
• Abstract summary: We present SituationalLLM, a novel approach that integrates structured scene information into an large language model.<n>By encoding objects, attributes, and relationships in a custom Scene Graph Language, SituationalLLM actively identifies gaps in environmental context and seeks clarifications during user interactions.<n> Experimental results indicate that SituationalLLM outperforms generic LLM baselines in task specificity, reliability, and adaptability.
• Score: 13.155859243167619
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Large language models (LLMs) have achieved remarkable success in text-based tasks but often struggle to provide actionable guidance in real-world physical environments. This is because of their inability to recognize their limited understanding of the user's physical context. We present SituationalLLM, a novel approach that integrates structured scene information into an LLM to deliver proactive, context-aware assistance. By encoding objects, attributes, and relationships in a custom Scene Graph Language, SituationalLLM actively identifies gaps in environmental context and seeks clarifications during user interactions. This behavior emerges from training on the Situational Awareness Database for Instruct-Tuning (SAD-Instruct), which combines diverse, scenario-specific scene graphs with iterative, dialogue-based refinements. Experimental results indicate that SituationalLLM outperforms generic LLM baselines in task specificity, reliability, and adaptability, paving the way for environment-aware AI assistants capable of delivering robust, user-centric guidance under real-world constraints.

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