Anqing Jiang

Orcid: 0000-0001-9187-830X

According to our database1, Anqing Jiang authored at least 16 papers between 2018 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
Unified Map Prior Encoder for Mapping and Planning.
CoRR, May, 2026

Do Open-Loop Metrics Predict Closed-Loop Driving? A Cross-Benchmark Correlation Study of NAVSIM and Bench2Drive.
CoRR, May, 2026

DiffSemanticFusion: Semantic Raster BEV Fusion for Autonomous Driving via Online Map Diffusion.
IEEE Robotics Autom. Lett., March, 2026

ETA-VLA: Efficient Token Adaptation via Temporal Fusion and Intra-LLM Sparsification for Vision-Language-Action Models.
CoRR, March, 2026

UniUncer: Unified Dynamic Static Uncertainty for End to End Driving.
CoRR, March, 2026

HiST-VLA: A Hierarchical Spatio-Temporal Vision-Language-Action Model for End-to-End Autonomous Driving.
CoRR, February, 2026

2025
DiffVLA++: Bridging Cognitive Reasoning and End-to-End Driving through Metric-Guided Alignment.
CoRR, October, 2025

AnchDrive: Bootstrapping Diffusion Policies with Hybrid Trajectory Anchors for End-to-End Driving.
CoRR, September, 2025

FlowDrive: Energy Flow Field for End-to-End Autonomous Driving.
CoRR, September, 2025

IRL-VLA: Training an Vision-Language-Action Policy via Reward World Model.
CoRR, August, 2025

DiffSemanticFusion: Semantic Raster BEV Fusion for Autonomous Driving via Online HD Map Diffusion.
CoRR, August, 2025

DiffVLA: Vision-Language Guided Diffusion Planning for Autonomous Driving.
CoRR, May, 2025

SparseMeXt: Unlocking the Potential of Sparse Representations for HD Map Construction.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2025

2022
A Reinforcement Learning Method for Optical Thin-Film Design.
IEICE Trans. Electron., 2022

2021
A Reinforcement learning method for Optical Thin-Film Design.
CoRR, 2021

2018
A new multilayer optical film optimal method based on deep q-learning.
CoRR, 2018


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