Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T17:50:21.307758Z
Paper Citation Record · LEDGER
As of 17 August 2026, this Paper Citation Record lists 73 of 73 outbound references and 2 inbound Pith citation observations for arXiv:2507.20342.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T17:50:21.307758Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T22:29:54.799574Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T19:30:07.209565Z
73 of 73 outbound references displayed
External citation measurements
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Observation 243f6754-5286-4862-90c0-d58ec7880b27 · outbound
VLMPlanner: Integrating Visual Language Models with Motion Planning Motional: nuplan challange
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VLMPlanner: Integrating Visual Language Models with Motion Planning GPT-4 Technical Report
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VLMPlanner: Integrating Visual Language Models with Motion Planning NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles
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VLMPlanner: Integrating Visual Language Models with Motion Planning Towards End-to-End Embodied Decision Making via Multi-modal Large Language Model: Explorations with GPT4-Vision and Beyond
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VLMPlanner: Integrating Visual Language Models with Motion Planning The Llama 3 Herd of Models
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VLMPlanner: Integrating Visual Language Models with Motion Planning DME-Driver: Integrating Human Decision Logic and 3D Scene Perception in Autonomous Driving
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Reference 21
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VLMPlanner: Integrating Visual Language Models with Motion Planning Imitation with Spatial-Temporal Heatmap: 2nd Place Solution for NuPlan Challenge
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VLMPlanner: Integrating Visual Language Models with Motion Planning EMMA: End-to-End Multimodal Model for Autonomous Driving
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Observation 9ca0b557-939f-4379-9161-8a3cecd51411 · outbound
VLMPlanner: Integrating Visual Language Models with Motion Planning Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Driving
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Observation 812ebcbd-766b-42f5-919f-00db0b041627 · outbound
VLMPlanner: Integrating Visual Language Models with Motion Planning NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking
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VLMPlanner: Integrating Visual Language Models with Motion Planning SurrealDriver: Designing LLM-powered Generative Driver Agent Framework based on Human Drivers' Driving-thinking Data
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