Integrated Multimodal AI System for Retrieval-Augmented Reasoning, Object Sensing, and Damage Analysis

arXiv:2608.08935 · cs.AI · Submitted 2026-08-09 · Read on arXiv

Kalelo Dukuray, Israel Pina, Evan Perez, Erika Ardiles-Cruz, Jie Wei

cs.AI

Submitted: 2026-08-09

Updated: 2026-08-11

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• RAG — 29× in this paper · explained in 3 episodes
• Knowledge Graph — 9× in this paper · explained in 8 episodes
• Failure Modes — 5× in this paper · explained in 3 episodes
• Foundation Model — 4× in this paper · explained in 3 episodes
• Grounding — 4× in this paper · explained in 3 episodes
• Hallucination — 4× in this paper · explained in 4 episodes
• Retrieval-Augmented Generation — 4× in this paper
• Retrieval-Augmented Generation (RAG) — 4× in this paper · explained in 21 episodes
• Multimodal Fusion — 3× in this paper · explained in 4 episodes
• Vision-language models — 3× in this paper · explained in 2 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Consistency — 2× in this paper · explained in 3 episodes
• Edge AI — 2× in this paper · explained in 2 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Harness — 2× in this paper · explained in 2 episodes
• Steering — 2× in this paper · explained in 2 episodes
• Vision Language Model — 2× in this paper
• Benchmark — 1× in this paper · explained in 2 episodes
• Contrastive Learning — 1× in this paper · explained in 9 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Dynamic Data-Driven Application Systems — 1× in this paper
• Fidelity — 1× in this paper · explained in 2 episodes
• Foundation Models — 1× in this paper · explained in 8 episodes
• Generator — 1× in this paper · explained in 2 episodes
• Localization — 1× in this paper · explained in 2 episodes
• Papers — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Robustness — 1× in this paper · explained in 6 episodes
• Segment Anything Model — 1× in this paper
• Segment Anything Model (SAM) — 1× in this paper · explained in 3 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Transformers — 1× in this paper · explained in 2 episodes
• Unmanned Aerial Vehicle — 1× in this paper
• Vision Foundation Models — 1× in this paper · explained in 2 episodes

Sources

• Investigating Vision-Language Model for Point Cloud-based Vehicle Classification
• NIDA-CLIFGAN: Natural Infrastructure Damage Assessment through Efficient Classification Combining Contrastive Learning, Information Fusion and Generative Adversarial Networks

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