Hong Wang
4 papers · Latest:
DeepSight: Long-Horizon World Modeling via Latent States Prediction for End-to-End Autonomous Driving
DeepSight improves end-to-end autonomous driving with a world model predicting long-horizon latent states and adaptive text reasoning.
Towards Lawful Autonomous Driving: Deriving Scenario-Aware Driving Requirements from Traffic Laws and Regulations
A novel LLM pipeline grounds traffic law reasoning in scenario taxonomy, accurately deriving driving requirements for autonomous vehicles.
Decoding the Delta: Unifying Remote Sensing Change Detection and Understanding with Multimodal Large Language Models
Delta-LLaVA is a new MLLM framework and benchmark (Delta-QA) for remote sensing change detection, overcoming "temporal blindness" with novel attention mechanisms.
Explanations from Large Language Models Make Small Reasoners Better
This paper shows how explanations generated by large language models can be used to train smaller, more efficient models that achieve superior reasoning accuracy and generate high-quality explanations.
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