BEVLM: Distilling Semantic Knowledge from LLMs into Bird's-Eye View Representations | ScienceToStartup | ScienceToStartup

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References (77)

[1]

Alpamayo-R1: Bridging Reasoning and Action Prediction for Generalizable Autonomous Driving in the Long Tail

2025Nvidia Yan Wang, Wenjie Luo et al.

[2]

Explanation-Driven Counterfactual Testing for Faithfulness in Vision-Language Model Explanations

2025Sihao Ding, Santosh Vasa et al.

[3]

Spatial Reasoning with Vision-Language Models in Ego-Centric Multi-View Scenes

Founder's Pitch

"BEVLM enhances autonomous driving by integrating LLMs with spatially consistent BEV representations for improved semantic reasoning and safety."

Autonomous Driving AI•Score: 2•View PDF ↗

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BEVLM: Distilling Semantic Knowledge from LLMs into Bird's-Eye View Representations

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References (77)

Founder's Pitch

"BEVLM enhances autonomous driving by integrating LLMs with spatially consistent BEV representations for improved semantic reasoning and safety."

Commercial Viability Breakdown

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BEVLM: Distilling Semantic Knowledge from LLMs into Bird's-Eye View Representations

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References (77)

Founder's Pitch

"BEVLM enhances autonomous driving by integrating LLMs with spatially consistent BEV representations for improved semantic reasoning and safety."

Commercial Viability Breakdown

Related Papers

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