Shows / Embodied AI 101
Embodied AI 101
Embodied AI 101 tracks the latest research at the intersection of AI and physical intelligence. Robotics, manipulation, world models, and the path from digital intelligence to embodied agents — each episode breaks down recent papers and advances in the field. We examine the methodology, real-world implications, and path to deployment. Covering robot learning, perception, control, and the fundamental challenge of grounding intelligence in the physical world. New episodes daily.
Episodes
- Embodied AI 101
Motion-Focused Latent Action for Cross-Embodiment VLA from Human Videos
Proposes a motion-focused latent action representation for cross-embodiment vision-language-action policies learned from human videos, accepted to IROS 2026.
- Embodied AI 101
ManiFlow: Manipulation via Rectified Flow
ManiFlow is a visuomotor imitation learning policy using consistency flow matching with a DiT-X architecture that generates high-quality actions in 1–2 steps…
- Embodied AI 101
RL-100: Toward Highly Reliable Real-World Robot Reinforcement Learning
RL-100 demonstrates highly reliable real-world RL manipulation achieving 900/900 success rates across 7 tasks with up to 250 consecutive trials without…
- Embodied AI 101
Genie Envisioner: A Unified World Foundation Platform for Robotic Manipulation
A video-diffusion world model trained on over 1 million manipulation episodes (3,000 hours) that includes an action model and neural simulator for closed-loop…
- Embodied AI 101
Bi-HIL: Bilateral Control-Based Multimodal Hierarchical Imitation Learning for Long-Horizon Contact-Rich Manipulation
Proposes a hierarchical imitation learning framework using bilateral control, subtask-level progress tracking, and keyframe memory to handle long-horizon…
- Embodied AI 101
From Passive Observer to Active Critic: Reinforcement Learning Elicits Process Reasoning for Robotic Manipulation
Uses reinforcement learning to improve process reasoning capabilities in robotic manipulation policies, shifting the model from passive observation to active…
- Embodied AI 101
ROVE: Unlocking Human Interventions for Humanoid Manipulation via Reinforcement Learning
ROVE leverages reinforcement learning to enable humanoid robots to benefit from human interventions during manipulation tasks.
- Embodied AI 101
ConstrainedMimic: Safe Humanoid Robot Motion Tracking
A control framework for safe humanoid robot motion tracking using RL policies with real-time constraint enforcement via kinematics, dynamics, and control…
- Embodied AI 101
REAL: Robust Extreme Agility via Spatio-Temporal Policy Learning and Physics-Guided Filtering
Introduces spatio-temporal policy learning combined with physics-guided filtering to achieve robust and extremely agile robot control.
- Embodied AI 101
HiFlow: Tokenization-Free Scale-Wise Autoregressive Policy Learning via Flow Matching
Introduces a tokenization-free autoregressive policy learning framework using flow matching across scales for robotic control.
- Embodied AI 101
Reactive Diffusion Policy: Slow-Fast Visual-Tactile Learning for Contact-Rich Manipulation
Introduces a slow-fast imitation learning framework combining diffusion-based planning with reactive tactile/force feedback for contact-rich manipulation…
- Embodied AI 101
SARM2 + SPIRAL: Multi-Task Reward Models and RL Refinement for Long-Horizon Dexterous Manipulation
Combines scalable autonomous reward modeling with RL-based refinement to improve vision-language-action policies on long-horizon dexterous manipulation tasks…
- Embodied AI 101
Co-VLA: Coordination-Aware Structured Action Modeling for Dual-Arm VLA Systems
Introduces coordination-aware structured action modeling for dual-arm robotic systems within a VLA framework. Addresses the unique challenges of bimanual…
- Embodied AI 101
ThinkingVLA: Interleaved Vision and Language Reasoning for Robotic Manipulation
Proposes interleaved vision and language reasoning for robotic manipulation within a VLA framework. Aims to improve instruction following and task performance…
- Embodied AI 101
Playful Agentic Robot Learning
Self-directed play combined with Code-as-Policy for reusable skill acquisition and downstream manipulation tasks.
- Embodied AI 101
Learning Unified Force and Position Control for Legged Loco-Manipulation
A unified RL policy for quadrupeds and humanoids that jointly handles force and position control without force sensors, enabling compliant behaviors…
- Embodied AI 101
Robots that Collaborate: Sequential Asymmetric Imitation for Learning Coupled Robot Policies
Explores imitation learning approaches for multi-robot systems, focusing on policy coupling through sequential asymmetric imitation to enable collaborative…
- Embodied AI 101
AstraBrain-WBC 0.5: A Humanoid Robot Cerebellum Foundation Model
A humanoid robot 'cerebellum' foundation model trained on 20,000 hours of human motion data that demonstrates scaling laws for robot motion control and enables…
- Embodied AI 101
SRL: Combining SLIP Model and Reinforcement Learning for Agile Robotic Jumping
Combines the Spring-Loaded Inverted Pendulum (SLIP) model with reinforcement learning to achieve agile jumping behaviors in robotic systems.
- Embodied AI 101
DataClaw0: Agentic Tailoring for Raw Multimodal Streams
A 9B model that filters noise from videos, GUI, and embodied data streams, reorganizing them into dense supervision via factual anchors and semantic synthesis…
- Embodied AI 101
ACE-Ego-0: Unifying Egocentric Human and Robotic Data for VLA Pretraining
Converts 6K+ hours of mixed human/robot egocentric video into robot pseudo-actions via camera-space alignment and reliability-aware loss, achieving 72.8% on…
- Embodied AI 101
VERA: Video-to-Action World Model Policy
A 14B-parameter video world model that converts predicted visual futures into embodiment-agnostic actions via Jacobian inverse-dynamics, enabling zero-shot…
- Embodied AI 101
GEN-1: Scaled Dexterous Manipulation Foundation Model
A dexterous manipulation foundation model trained on 500k hours of real-world bimanual data that handles deformable objects such as cardboard folding and screw…
- Embodied AI 101
Efficient Hybrid SE(3)-Equivariant Visuomotor Flow Policy via Spherical Harmonics for Robot Manipulation
Develops an SE(3)-equivariant flow-based visuomotor policy leveraging spherical harmonics for efficient and geometrically consistent robot manipulation.
- Embodied AI 101
Cortical Policy: A Dual-Stream View Transformer for Robotic Manipulation
Introduces a dual-stream transformer architecture inspired by cortical visual processing for learning robotic manipulation policies.
- Embodied AI 101
VisualClaw: A Self-Evolving Wearable Vision Agent
An edge-filtered video streaming agent that evolves skills from memory and runs on smart glasses, reducing API costs by 98%, accompanied by the VisualClawArena…
- Embodied AI 101
Kairos: A Native World Model Stack for Physical AI
A 4B unified architecture for world understanding, generation, and action with hybrid linear attention enabling real-time edge inference across embodiments…
- Embodied AI 101
DragMesh-2: A Contact-Driven Framework for Dexterous Hand–Object Interaction
A framework that trains a 51-DoF dexterous hand to open drawers and doors using only physical contact without requiring tactile sensors.
- Embodied AI 101
Guava: A Universal Harness for Robot Manipulation
A 4B open-source VLA-style model trained on fewer than 2K simulation trajectories that matches closed frontier systems on real-world manipulation tasks with…
- Embodied AI 101
Geometric Action Model for Robot Policies
A new geometric action model for robot manipulation policies that focuses on structured action representations to improve policy learning and generalization.
- Embodied AI 101
ENPIRE: Physical AutoResearch with a Fleet of 8 Robots
ENPIRE demonstrates fully autonomous physical AutoResearch where Codex agents control a fleet of 8 robots overnight, self-improving through real hardware…
- Embodied AI 101
MolmoAct2: An Open Foundation Model for Real-World Robotics
An open VLA-style robotics foundation model featuring open weights, open dataset, open action tokenizer, and a depth-reasoning variant; designed to enable…
- Embodied AI 101
Hy-Embodied-0.5-VLA: A Massive Bimanual Teleoperation Dataset for Vision-Language-Action
Released a massive bimanual robot manipulation dataset with 2,163 hours and 250K+ episodes across 70+ tasks, along with a compatible VLA model for multi-view…
- Embodied AI 101
Q-Guided Flow: Test-Time Gradient Guidance of Flow Policies
New framework for guided flow-matching policies that improves long-horizon robotic control and sample efficiency.
- Embodied AI 101
Flow Reversal Steering: Guiding Diffusion-Based Robot Policies with High-Level Reasoning
Introduces flow reversal steering to guide diffusion-based vision-language-action models with high-level VLM reasoning and enables RL directly in the diffusion…
- Embodied AI 101
Test-Time Compute Scaling for Robot Policies (DIRECT)
Larger models + more thinking + more context improve performance on some prompts but not others; a learned router enables better performance/latency trade-offs.
- Embodied AI 101
LabVLA: Bringing Vision-Language-Action to the Chemistry Lab
RoboGenesis generates 10K+ lab scenes across 16 robot embodiments; LabVLA (Qwen3-VL + DiT flow-matching) achieves 71.1% success on LabUtopia and transfers to…
- Embodied AI 101
Humanoid-GPT: A Foundation Model for Zero-Shot Humanoid Control
GPT-style Transformer pretrained on 2 billion motion frames that achieves agile, generalist zero-shot control on a real Unitree G1 humanoid for tasks like…
- Embodied AI 101
CHORUS: Decentralized Multi-Robot Collaboration with a Single Shared VLA Model
Finetunes a single Vision-Language-Action (VLA) foundation model so that any robot in a team can control any other. Outperforms both per-robot specialists and…
- Embodied AI 101
RISE: Self-Improving Robot Policy with Compositional World Model
Trains a compositional world model on real robot data to enable closed-loop policy improvement via future prediction and progress evaluation, bypassing both…
- Embodied AI 101
EmbodiedOneVision: Interleaved Vision-Text-Action Pretraining for General Robot Control
Open-source 3B unified embodied foundation model trained on 1.5M interleaved vision-text-action samples for perception, planning, and acting.
- Embodied AI 101
Robix: A Unified Model for Robot Interaction, Reasoning and Planning
A single vision-language model that unifies reasoning, task planning, and human-robot interaction for complex instructions and long-horizon tasks.
- Embodied AI 101
Robotic World Model: Learning to Simulate for Robust Robot Control
Presents a neural network-based world model for model-based reinforcement learning in robotics, focusing on sim-to-real transfer for quadrupedal and humanoid…
- Embodied AI 101
AnchorWorld: Embodied Egocentric World Simulation with View-based Evolution Customization
Embodied egocentric simulation framework that controls first-person worlds with 3D human motion and customizes evolving scenes via pose-anchored views.
- Embodied AI 101
ArtiFixer: Few-Step Diffusion for 3D Scene Reconstruction
Few-step auto-regressive diffusion model that converts broken 3D reconstructions into fully realized scenes, outperforming prior methods by 1-3 dB PSNR.
- Embodied AI 101
Deployment-Time Memorization in Foundation-Model Agents
Examines memorization phenomena that occur during deployment of foundation model agents in practical applications.
- Embodied AI 101
Adversarial Machine Learning: Taxonomy, Threat Models, and Mitigation Strategies in Deep Neural Networks
Focuses on security aspects of deep neural networks, providing taxonomy and mitigation strategies for adversarial attacks.
- Embodied AI 101
SoCRATES: Evaluating LLM Mediators in Conflict Scenarios
First comprehensive framework for evaluating LLM mediators in real-time, emotional, socio-cognitive scenarios.
- Embodied AI 101
Unembedding Matrix as a Feature Lens: Unlocking Better Text Embeddings
Improves embedding quality without extra training by using the unembedding matrix as a feature lens for text embeddings.
- Embodied AI 101
LeanMarathon: Autonomous Formalization of Math Proofs on Erdős Problems
Presents an autonomous system for formalizing mathematical proofs, specifically targeting Erdős problems. Demonstrates automated proof formalization…
- Embodied AI 101
Deep Research Agents: Survey and Roadmap for Autonomous AI Research
Provides a comprehensive taxonomy, benchmarks, and future directions for autonomous AI research agents. Examines systematic approaches to developing agents…
- Embodied AI 101
Cosmos 3: Omnimodal World Models for Physical AI
Omnimodal world models explicitly designed for Physical AI and robotics applications. Enables improved simulation and control for robotic systems through…
- Embodied AI 101
Humanoid-GPT: GPT-Style Transformer for Zero-Shot Dynamic Humanoid Control
GPT-style Transformer trained on 2 billion motion frames enabling zero-shot dynamic humanoid control for tasks like soccer, dancing, and digging on real…
- Embodied AI 101
Bending Paper, Shaping Dexterity: The Robotic Origami Challenge
New IROS benchmark providing 500+ teleoperation episodes and physically accurate simulation assets for training policies that outperform human origami experts.
- Embodied AI 101
GraspGen-X: A Foundation Model for Zero-Shot 6-DoF Grasping
First foundation model for zero-shot grasping trained on billions of simulated grasps, enabling generalized manipulation without task-specific training.
- Embodied AI 101
When Does Deep RL Beat Calibrated Baselines?
Benchmark study examining when deep reinforcement learning outperforms calibrated baseline methods in adaptive resource control tasks.
- Embodied AI 101
Training Deep Networks as Random Effects: An Optimization–Inference Duality
Explores training dynamics of deep neural networks through a statistical lens, examining the duality between optimization and inference perspectives.
- Embodied AI 101
Generative Depth Supervision for Embodied Vision-Language Models
Vision-language model that adds generative depth prediction during pre-training for physical grounding; achieves SOTA on embodied benchiments and transfers…
- Embodied AI 101
PointWorld: Scaling 3D World Models for In-The-Wild Robotic Manipulation
Presents a 3D point-cloud-based world model trained on mixed real/sim data that enables zero-shot grasping and articulated object handling on real robots by…
- Embodied AI 101
LocateAnything: Fast and High-Quality Vision-Language Grounding with Parallel Box Decoding
NVIDIA Research presents LocateAnything, a unified generative grounding and detection framework based on Parallel Box Decoding (PBD). Unlike prior VLMs that…