ML Systems Wiki Knowledge base for ML systems, autonomy, and embodied AI
ESC

Tags

239 tags across the wiki

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 vlm

Alpamayo-R1: Bridging Reasoning and Action Prediction for Generalizable Autonomous Driving in the Long Tail
source-summary

Yan Wang, Wenjie Luo, Junjie Bai, Yulong Cao, Marco Pavone + 37 co-authors (NVIDIA), arXiv, 2025. 📄 **[Read on arXiv](https://arxiv.org/abs/2511.00088)** Alpamayo-R1 is NVIDIA's production-grade Vision-Language-Action (…
AlphaDrive: Unleashing the Power of VLMs in Autonomous Driving via Reinforcement Learning and Reasoning
source-summary

Bo Jiang, Shaoyu Chen, Qian Zhang, Wenyu Liu, Xinggang Wang, arXiv, 2025. 📄 **[Read on arXiv](https://arxiv.org/abs/2503.07608)** AlphaDrive is the first application of GRPO (Group Relative Policy Optimization) reinforc…
DriveGPT4: Interpretable End-to-End Autonomous Driving via Large Language Model
source-summary

Zhenhua Xu, Yujia Zhang, Enze Xie, Zhen Zhao, Yong Guo, Kwan-Yee K. Wong, Zhenguo Li, Hengshuang Zhao, IEEE Robotics and Automation Letters, 2024. 📄 **[Read on arXiv](https://arxiv.org/abs/2310.01412)** DriveGPT4 applie…
DriveLM: Driving with Graph Visual Question Answering
source-summary

📄 **[Read on arXiv](https://arxiv.org/abs/2312.14150)** DriveLM formalizes driving reasoning as Graph Visual Question Answering (GVQA), where QA pairs are connected via logical dependencies forming a reasoning graph tha…
DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models
source-summary

📄 **[Read on arXiv](https://arxiv.org/abs/2402.12289)** DriveVLM proposes a hierarchical approach to integrating Vision-Language Models into autonomous driving, emphasizing scene understanding and multi-level planning r…
EMMA: End-to-End Multimodal Model for Autonomous Driving
source-summary

📄 **[Read on arXiv](https://arxiv.org/abs/2410.23262)** EMMA is Waymo's industry-scale demonstration of the "everything as language tokens" paradigm for autonomous driving. A single large multimodal foundation model uni…
Flamingo: a Visual Language Model for Few-Shot Learning
paper

📄 **[Read on arXiv](https://arxiv.org/abs/2204.14198)** Flamingo, developed by DeepMind, is a family of visual language models that extend the in-context few-shot learning ability of large language models to multimodal…
Foundation Models
concept

Foundation models -- large models pretrained on broad data and adapted to downstream tasks -- are reshaping autonomous driving. This page tracks how LLMs, VLMs, and diffusion models influence autonomy, and examines the…
Orion Holistic End To End Autonomous Driving By Vision Language Instructed Action Generation
source-summary

📄 **[Read on arXiv](https://arxiv.org/abs/2503.19755)** ORION bridges the reasoning-action gap in driving VLAs through a three-component architecture consisting of QT-Former (visual encoding), an LLM reasoning core, and…
PaLM-E: An Embodied Multimodal Language Model
source-summary

📄 **[Read on arXiv](https://arxiv.org/abs/2303.03378)** PaLM-E is a 562-billion parameter embodied multimodal language model created by Google that injects continuous sensor observations (images, point clouds, robot sta…
Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Driving
source-summary

📄 **[Read on arXiv](https://arxiv.org/abs/2410.22313)** Two dominant paradigms exist in autonomous driving: large vision-language models (LVLMs) with strong reasoning but poor trajectory precision, and end-to-end (E2E)…
SimLingo: Vision-Only Closed-Loop Autonomous Driving with Language-Action Alignment
source-summary

📄 **[Read on arXiv](https://arxiv.org/abs/2503.09594)** Many driving VLM efforts improve language understanding (VQA, scene descriptions) but sacrifice actual driving performance. A model can correctly answer questions…
Vision Language Action
concept

This page tracks the bridge from multimodal understanding to action generation, informed by the AutoVLA corpus of 18 papers spanning 2018–2025. A VLA system consumes visual context and language-conditioned intent, then…
VLA and Driving
source-program

This queue spans general VLA foundations and driving-specific multimodal action papers. The AutoVLA corpus (18 papers, 2018–2025) provides the most comprehensive coverage of how language-vision models have been applied…
VLP: Vision Language Planning for Autonomous Driving
source-summary

📄 **[Read on arXiv](https://arxiv.org/abs/2401.05577)** VLP (Vision Language Planning) by Pan et al. (CVPR 2024) represents a fundamentally different approach to using language in autonomous driving compared to instruct…