Cover Image

Closed-Loop Supervised Fine-Tuning of Tokenized Traffic Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Zhejun, Karkus, Peter, Igl, Maximilian, Ding, Wenhao, Chen, Yuxiao, Ivanovic, Boris, Pavone, Marco
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

RoaD: Rollouts as Demonstrations for Closed-Loop Supervised Fine-Tuning of Autonomous Driving Policies
by: Garcia-Cobo, Guillermo, et al.
Published: (2025)

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes
by: Yang, Jiawei, et al.
Published: (2024)

Gen-Drive: Enhancing Diffusion Generative Driving Policies with Reward Modeling and Reinforcement Learning Fine-tuning
by: Huang, Zhiyu, et al.
Published: (2024)

DTPP: Differentiable Joint Conditional Prediction and Cost Evaluation for Tree Policy Planning in Autonomous Driving
by: Huang, Zhiyu, et al.
Published: (2023)

RealGen: Retrieval Augmented Generation for Controllable Traffic Scenarios
by: Ding, Wenhao, et al.
Published: (2023)

Efficient Multi-Camera Tokenization with Triplanes for End-to-End Driving
by: Ivanovic, Boris, et al.
Published: (2025)

LoRD: Adapting Differentiable Driving Policies to Distribution Shifts
by: Diehl, Christopher, et al.
Published: (2024)

Promptable Closed-loop Traffic Simulation
by: Tan, Shuhan, et al.
Published: (2024)

Producing and Leveraging Online Map Uncertainty in Trajectory Prediction
by: Gu, Xunjiang, et al.
Published: (2024)

Accelerating Online Mapping and Behavior Prediction via Direct BEV Feature Attention
by: Gu, Xunjiang, et al.
Published: (2024)

Back to Blackwell: Closing the Loop on Intransitivity in Multi-Objective Preference Fine-Tuning
by: Zhang, Jiahao, et al.
Published: (2026)

Learning Multiple Initial Solutions to Optimization Problems
by: Sharony, Elad, et al.
Published: (2024)

Supervised Fine-Tuning Needs to Unlock the Potential of Token Priority
by: Shen, Zhanming, et al.
Published: (2026)

Sample-Efficient Safety Assurances using Conformal Prediction
by: Luo, Rachel, et al.
Published: (2021)

LoRA3D: Low-Rank Self-Calibration of 3D Geometric Foundation Models
by: Lu, Ziqi, et al.
Published: (2024)

Anchored Supervised Fine-Tuning
by: Zhu, He, et al.
Published: (2025)

On-Policy RL Meets Off-Policy Experts: Harmonizing Supervised Fine-Tuning and Reinforcement Learning via Dynamic Weighting
by: Zhang, Wenhao, et al.
Published: (2025)

Surprise Potential as a Measure of Interactivity in Driving Scenarios
by: Ding, Wenhao, et al.
Published: (2025)

Parallelized Spatiotemporal Binding
by: Singh, Gautam, et al.
Published: (2024)

Parameter-Efficient Fine-Tuning for Foundation Models
by: Zhang, Dan, et al.
Published: (2025)

On the Entropy Dynamics in Reinforcement Fine-Tuning of Large Language Models
by: Wang, Shumin, et al.
Published: (2026)

Structural Priors and Modular Adapters in the Composable Fine-Tuning Algorithm of Large-Scale Models
by: Wang, Yuxiao, et al.
Published: (2025)

Closed-Loop Neural Operator-Based Observer of Traffic Density
by: Harting, Alice, et al.
Published: (2025)

Matching Features, Not Tokens: Energy-Based Fine-Tuning of Language Models
by: Jelassi, Samy, et al.
Published: (2026)

Diversity in Large Language Models under Supervised Fine-Tuning
by: Klypa, Roman, et al.
Published: (2026)

Preserving Diversity in Supervised Fine-Tuning of Large Language Models
by: Li, Ziniu, et al.
Published: (2024)

LIFT: LLM-Based Pragma Insertion for HLS via GNN Supervised Fine-Tuning
by: Prakriya, Neha, et al.
Published: (2025)

Learning While Staying Curious: Entropy-Preserving Supervised Fine-Tuning via Adaptive Self-Distillation for Large Reasoning Models
by: Wang, Hao, et al.
Published: (2026)

Erasing the Bias: Fine-Tuning Foundation Models for Semi-Supervised Learning
by: Gan, Kai, et al.
Published: (2024)

Rotation-Preserving Supervised Fine-Tuning
by: Jin, Hangzhan, et al.
Published: (2026)

RIFT: Group-Relative RL Fine-Tuning for Realistic and Controllable Traffic Simulation
by: Chen, Keyu, et al.
Published: (2025)

Proximal Supervised Fine-Tuning
by: Zhu, Wenhong, et al.
Published: (2025)

A Layer-wise Analysis of Supervised Fine-Tuning
by: Zhao, Qinghua, et al.
Published: (2026)

Causal Composition Diffusion Model for Closed-loop Traffic Generation
by: Lin, Haohong, et al.
Published: (2024)

DGLight: DQN-Guided GRPO Fine-Tuning of Large Language Models for Traffic Signal Control
by: Yu, Chenbo
Published: (2026)

UFT: Unifying Supervised and Reinforcement Fine-Tuning
by: Liu, Mingyang, et al.
Published: (2025)

D3MES: Diffusion Transformer with multihead equivariant self-attention for 3D molecule generation
by: Zhang, Zhejun, et al.
Published: (2025)

VARAN: Variational Inference for Self-Supervised Speech Models Fine-Tuning on Downstream Tasks
by: Diatlova, Daria, et al.
Published: (2025)

Parameter-Efficient Fine-Tuning with Circulant and Diagonal Vectors
by: Ding, Xinyu, et al.
Published: (2025)

Trajeglish: Traffic Modeling as Next-Token Prediction
by: Philion, Jonah, et al.
Published: (2023)