Papers with open-world tasks

2 papers
VistaWise: Building Cost-Effective Agent with Cross-Modal Knowledge Graph for Minecraft (2025.emnlp-main)

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Challenge: Large language models (LLMs) have shown significant promise in embodied decision-making tasks within virtual open-world environments, but lack domain-specific knowledge.
Approach: They propose a cost-effective agent framework that integrates cross-modal domain knowledge and finetunes a dedicated object detection model for visual analysis.
Outcome: The proposed framework reduces the requirement for domain-specific training data from millions of samples to a few hundred.
Meta-Tool: Unleash Open-World Function Calling Capabilities of General-Purpose Large Language Models (2025.acl-long)

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Challenge: Large language models struggle with addressing diverse user inquiries in open-world tasks.
Approach: They propose a plug-and-play tool retrieval system for LLMs to access external tool library and use retrieved tools to solve user's problem.
Outcome: The proposed model improves on a finetuned version of LLaMA-3.1 and 2,800 dialogues and 7,361 tools spanning ten distinct test categories.

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