5 papers
Beyond Scene Priors: Fine-Grained Traffic Scene Reasoning with Benchmarking and Query-Guided Small-Object Focus
Waikit Xiu, Qiang Lu, Zian Wang +4
In safety-critical traffic scenarios, answering complex questions relies on minute, localized visual cues. However, standard Multimodal Large Language Models (MLLMs) tend to over-a…
LASAR: Towards Spatio-temporal Reasoning with Latent Cognitive Map
Jinzhou Tang, Sidi Liu, Waikit Xiu +2
A fundamental challenge in embodied AI is verifying if agents build internal models of spatial structure or merely learn to mimic task-specific expert trajectories. This is critica…
Traffic-MLLM: Curiosity-Regularized Supervised Learning for Traffic Scenario Case-Based Reasoning
Waikit Xiu, Qiang Lu, Bingchen Liu +2
For safe and robust autonomous driving, decision-making systems must effectively leverage past experiences to handle the inherent long-tail of traffic scenarios. Case-Based Reasoni…
Beyond Pixels: Introducing Geometric-Semantic World Priors for Video-based Embodied Models via Spatio-temporal Alignment
Jinzhou Tang, Jusheng zhang, Sidi Liu +3
Achieving human-like reasoning in deep learning models for complex tasks in unknown environments remains a critical challenge in embodied intelligence. While advanced vision-langua…
Contrastive Learning-Driven Traffic Sign Perception: Multi-Modal Fusion of Text and Vision
Qiang Lu, Waikit Xiu, Xiying Li +2
Traffic sign recognition, as a core component of autonomous driving perception systems, directly influences vehicle environmental awareness and driving safety. Current technologies…