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paper 114 autonomous-driving 92 foundation-model 55 transformer 53 vla 49 planning 42 robotics 41 computer-vision 36 perception 32 ilya-30 29 multimodal 29 nlp 26 end-to-end 24 language-modeling 24 llm 17 reasoning 17 imitation-learning 16 3d-occupancy 15 vlm 15 bev 14 diffusion 13 e2e 12 reinforcement-learning 12 world-model 12 chain-of-thought 10 benchmark 9 scaling 9 cross-embodiment 7 driving 6 gaussian-splatting 6 generative-models 6 image-classification 6 information-theory 6 questions 6 self-supervised 6 sources 6 alignment 5 attention 5 cnn 5 foundation 5 knowledge-distillation 5 language-model 5 prediction 5 simulation 5 evaluation 4 image-generation 4 instruction-tuning 4 mixture-of-experts 4 rnn 4 sequence-to-sequence 4 sparse-representation 4 video-prediction 4 explainability 3 flow-matching 3 lstm 3 map 3 occupancy 3 open-source 3 semantic-segmentation 3 sequence-modeling 3 trajectory-prediction 3 vectorized-representation 3 3d-detection 2 3d-perception 2 3d-reconstruction 2 action-representation 2 autonomy 2 autoregressive 2 bimanual 2 closed-loop 2 complexity-theory 2 dataset 2 deployment 2 distributed-training 2 efficient-inference 2 embodied 2 fine-tuning 2 foundation-models 2 foundational 2 gaussian-representation 2 generation 2 generative 2 human-interaction 2 humanoid 2 manipulation 2 memory-augmented-networks 2 ml 2 multi-camera 2 multilingual 2 object-detection 2 parameter-efficient-fine-tuning 2 prompting 2 real-time 2 regularization 2 relational-reasoning 2 residual-networks 2 rlhf 2 scaling-laws 2 segmentation 2 self-improvement 2 self-supervised-learning 2 state-space 2 systems 2 thermodynamics 2 vision-language-model 2 vision-transformer 2 visual-question-answering 2 zero-shot 2 3d 1 3d-scene 1 3d-semantic-occupancy 1 agenda 1 agentic 1 agi 1 algorithmic-information-theory 1 algorithmic-randomness 1 asynchronous 1 attention-mechanism 1 batch 1 bayesian-inference 1 behavior-forecasting 1 camera-fusion 1 classifier-guidance 1 combinatorial-optimization 1 comparison 1 compression 1 computability 1 concept 1 contrastive-learning 1 control 1 convolutional-neural-networks 1 corpus 1 course 1 data-collection 1 decoupled 1 deep-learning 1 denoising 1 depth-estimation 1 dexterous-manipulation 1 differentiable-programming 1 diffusion-policy 1 diffusion-transformer 1 dilated-convolutions 1 dropout 1 efficient 1 embodied-ai 1 embodiment 1 emergent-abilities 1 end-to-end-learning 1 evaluation-metric 1 few-shot 1 few-shot-learning 1 foundations 1 frontend 1 gaussian 1 gaussian-rendering 1 generalist-agent 1 generalization 1 gpu-training 1 graph-neural-networks 1 grounding 1 grpo 1 hierarchical 1 high-frequency-control 1 hosting 1 ilya 1 image-captioning 1 image-text-retrieval 1 in-context-learning 1 inductive-bias 1 intelligence-measurement 1 interactive-annotation 1 interactive-segmentation 1 knowledge-preservation 1 kolmogorov-complexity 1 lanegcn 1 locomotion 1 machine-translation 1 mamba 1 mdl 1 message-passing 1 minimum-description-length 1 model-parallelism 1 model-predictive-control 1 model-selection 1 modular 1 molecular-property-prediction 1 multi-embodiment 1 multi-task 1 natural-language 1 neural-radiance-fields 1 neuro-symbolic 1 obsidian 1 open-world 1 optimization 1 orchestration 1 parallel-architecture 1 parameter-efficient 1 permutation-invariance 1 personalization 1 physical-ai 1 pipeline-parallelism 1 pointer-mechanism 1 privileged-supervision 1 probabilistic-planning 1 proprioception 1 quantization 1 queue 1 radar 1 recurrent-neural-networks 1 representation-learning 1 scene-understanding 1 search 1 seminal 1 sensor-fusion 1 set-modeling 1 siamese-networks 1 simulator 1 source 1 sparse-models 1 spatial-reasoning 1 speech-recognition 1 survey 1 synthesis 1 taxonomy 1 temporal 1 temporal-modeling 1 thesis 1 tokenization 1 tool-use 1 training 1 uniad 1 unified-stack 1 vanishing-gradients 1 variational-autoencoders 1 video-generation 1 video-understanding 1 visual-traces 1 vit 1

Pages tagged imitation-learning

ChauffeurNet: Learning to Drive by Imitating the Best and Synthesizing the Worst
source-summary

📄 **[Read on arXiv](https://arxiv.org/abs/1812.03079)** Bansal, Krizhevsky, Ogale (Waymo Research), RSS, 2019. - [Paper](https://arxiv.org/abs/1812.03079) ChauffeurNet is Waymo's mid-level imitation learning system that…
Covla Comprehensive Vision Language Action Dataset For Autonomous Driving
paper

📄 **[Read on arXiv](https://arxiv.org/abs/2408.10845)** Autonomous driving systems face the "long tail" problem -- handling countless rare and complex driving scenarios beyond common situations. While traditional rule-b…
DriveAdapter: Breaking the Coupling Barrier of Perception and Planning in End-to-End Autonomous Driving
paper

📄 **[Read on arXiv](https://arxiv.org/abs/2308.00398)** DriveAdapter (Jia et al., ICCV 2023) identifies and addresses a fundamental structural problem in end-to-end autonomous driving: the tight coupling between percept…
End-to-end Driving via Conditional Imitation Learning
source-summary

📄 **[Read on arXiv](https://arxiv.org/abs/1710.02410)** This paper introduces conditional imitation learning for end-to-end autonomous driving, where a neural network policy is conditioned on a discrete high-level comma…
GR-2: A Generative Video-Language-Action Model with Web-Scale Knowledge for Robot Manipulation
paper

📄 **[Read on arXiv](https://arxiv.org/abs/2410.06158)** GR-2 is a generalist robot manipulation agent from ByteDance Research that leverages large-scale video-language pretraining to build a world model for robotic cont…
Hydra-MDP: End-to-End Multimodal Planning with Multi-Target Hydra-Distillation
paper

:page_facing_up: **[Read on arXiv](https://arxiv.org/abs/2406.06978)** Hydra-MDP addresses a fundamental limitation of imitation learning for autonomous driving: standard behavior cloning learns only to mimic human demo…
Learning by Cheating
source-summary

📄 **[Read on arXiv](https://arxiv.org/abs/1912.12294)** Learning by Cheating introduces a two-stage training paradigm for end-to-end autonomous driving that has become one of the most influential design patterns in the…
LLARVA: Vision-Action Instruction Tuning Enhances Robot Learning
paper

📄 **[Read on arXiv](https://arxiv.org/abs/2406.11815)** LLARVA addresses the "embodiment gap" between large multimodal models (LMMs) and robotic control. While VLMs trained on internet-scale data excel at visual underst…
Octo An Open Source Generalist Robot Policy
paper

📄 **[Read on arXiv](https://arxiv.org/abs/2405.12213)** Octo is a transformer-based generalist robot policy trained on 800,000 robot trajectories from the Open X-Embodiment dataset, spanning 25 diverse datasets and mult…
Robocat A Self Improving Generalist Agent For Robotic Manipulation
paper

📄 **[Read on arXiv](https://arxiv.org/abs/2306.11706)** RoboCat, developed by Google DeepMind, is a multi-embodiment, multi-task generalist agent for robotic manipulation built on a transformer-based architecture. The p…
RoboFlamingo: Vision-Language Foundation Models as Effective Robot Imitators
paper

📄 **[Read on arXiv](https://arxiv.org/abs/2311.01378)** RoboFlamingo addresses the question of whether publicly available vision-language models (VLMs) can serve as effective backbones for robot imitation learning, with…
RoboVLMs: What Matters in Building Vision-Language-Action Models
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📄 **[Read on arXiv](https://arxiv.org/abs/2412.14058)** RoboVLMs is a large-scale empirical study from Tsinghua University, ByteDance Research, and collaborators that systematically investigates the design principles fo…
RT-H: Action Hierarchies Using Language
paper

📄 **[Read on arXiv](https://arxiv.org/abs/2403.01823)** RT-H (Robot Transformer with Action Hierarchies) introduces a hierarchical approach to multi-task robot control that uses natural language as an intermediate repre…
Scaling Cross Embodied Learning One Policy For Manipulation Navigation Locomotion And Aviation
paper

📄 **[Read on arXiv](https://arxiv.org/abs/2408.11812)** CrossFormer addresses a fundamental limitation in robot learning: the requirement for specialized policies for each robotic platform. Traditional approaches train…
Think Twice before Driving: Towards Scalable Decoders for End-to-End Autonomous Driving
paper

📄 **[Read on arXiv](https://arxiv.org/abs/2305.06242)** Think Twice (Jia et al., 2023) addresses a fundamental imbalance in end-to-end autonomous driving: while the community has invested heavily in sophisticated encode…
Unleashing Large-Scale Video Generative Pre-training for Visual Robot Manipulation (GR-1)
paper

📄 **[Read on arXiv](https://arxiv.org/abs/2312.13139)** GR-1 addresses a fundamental bottleneck in robot learning: the scarcity of diverse, high-quality robot demonstration data. The key insight is that robot trajectori…