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RILA: A Radar-Native Structured Interface from Sparse mmWave Point Clouds to Large Language Models
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Proposes RILA, a radar-native structured interface that converts sparse mmWave point clouds into LLM-compatible representations for radar-to-language tasks.
Problem
Existing radar-to-language pipelines map sparse mmWave point clouds into global clip features or discrete token codes that are weakly matched to the structure LLMs expect.
Approach
A radar-native structured interface layer that converts sparse mmWave point clouds into structured representations for LLM adaptation, rather than global clip features or discrete token codes.
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