Papers by Andrea Sensi
Training Multi-Modal LLMs through Dialogue Planning for HRI (2025.findings-acl)
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| Challenge: | Existing approaches to enhance Multi-Modal Large Language Models (MLLMs) with explicit dialogue planning improves response accuracy and quality, and allows models trained in one language to transfer effectively to another. |
| Approach: | They propose an approach that enhances Multi-Modal Large Language Models with a novel explicit dialogue planning phase that allows agents to refine their understanding of ambiguous commands. |
| Outcome: | The proposed approach reduces hallucinations and improves task feasibility by fine-tuning and assessing Multi-Modal models in human-robot interaction scenarios. |