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Morning Edition · Tue, Sep 1, 2026
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RESEARCH · arXiv
DELE-w0.5: Inferring Action from Future Latent State for Robotic Manipulation

DELE-w0.5 infers robot actions from compact future latent state, achieving 62.5% overall full-task success and 81.3% macro ordered-stage progress in 640 real-robot trials.

Fenghao Lei et al.5h agorel 0.64
RESEARCH · arXiv
PAVE: Predictive Alignment and Value-Guided Evolution for World-Action Policies

PAVE achieves the strongest overall performance across the three simulation benchmarks while preserving the direct actor’s online execution path.

Botong Zhao et al.5h agorel 0.64
RESEARCH · arXiv
AnyWorld: Factorized Egocentric World Models for Cross-Embodiment Generalization

AnyWorld factorizes action, camera, and embodiment to generate robot-native rollouts from human videos, improving manipulation on RoboCasa GR1 and a real IRON humanoid robot.

Cheng Chen et al.5h agorel 0.62
RESEARCH · arXiv
Motus2: A Self-Evolving General World Model for Dexterous Manipulation

Motus2 couples a policy, simulator, and evaluator into a closed decision-and-learning loop, advancing from monocular to synchronized stereo egocentric data for self-evolving dexterous manipulation.

Hongzhe Bi et al.5h agorel 0.62
FROM X · techniahqrobot
Humanoid robotics has its own language. Here are 30 acronyms you will see constantly API = Application Programming In…

Humanoid robotics acronyms list 30 terms, including API, BC, CoM, RL, ROS 2, SLAM, and ZMP, commonly seen in research papers, demos, and technical specs.

13h agorel 0.62
RESEARCH · arXiv
TrAct: Bridging Robot Control and Visual Prediction with Visual Tracks

TrAct improves success rates from 27% to 55% in simulation and from 49% to 76% on real-world tasks compared with the strong VLA baseline π0.5.

Zhi Cao et al.5h agorel 0.62
RESEARCH · arXiv
CometVLA: Co-Training on an Embodied Data Pyramid towards Physical Understanding

CometVLA co-trains on the embodied data pyramid and consistently outperforms strong VLA baselines on real-world manipulation tasks and RoboTwin simulation.

Hanwen Wan et al.5h agorel 0.61
RESEARCH · arXiv
FetchMan: Learning Visual Humanoid Loco-Manipulation Policies from Simulated Experiences

FetchMan reaches 73.3% success zero-shot on a real Unitree G1 for single-object reach-and-pick across unseen scenes after Flow-GRPO refining synthetic cloning.

Omar Rayyan et al.5h agorel 0.61
RESEARCH · arXiv
AcrossWAM1.0:A Modular Latent World-Action Stack for Compact Robot Policies

AcrossWAM1.0 modularizes latent world-action policies and, on 2,000 paired LIBERO episodes, retains 97.45% success versus 98.00% for the 2B model with 42.4% fewer parameters.

Yafei Zhang & Nan Wu5h agorel 0.61
FROM X · hiroki_research
[ New Predictive VLA policy published! ] I would like to share our recent study just published several days ago on arXi…

PredVLA, a 0.68M-parameter predictive-coding RNN with no robot-data pretraining, achieves a comparable success rate to OpenVLA by predicting sensorimotor dynamics and using prediction errors for action inference.

4h agorel 0.61
FROM X · arjunjain
Wanna dip into end-to-end driving and world models? Our team at @FastCodeAI recommends reading these papers to get star…
4h agorel 0.56
FROM X · menlotimes
What if robots could learn more from video, and need far less human demonstration data? Perceptron @perceptroninc has …

Perceptron’s open-sourced Isaac 0.5, a 36-billion-parameter embodied foundation model, cut teleoperation needed for target action loss from about 5,900 hours to 28 hours, a 210× reduction.

15h agorel 0.56
FROM X · botnewsai
@weloverobotics @nvidia @GeneralistAI They overlap at the human-demo layer, but they are solving different parts of the…

Hydra-0 is a world/action model, not a GEN-1.5 competitor; it uses human demos to supply desired object motion and can generate compatible robot motion.

6h agorel 0.54
DISCUSSION · GhostMesh48
AeonMosaic - A pleromic modular robot in which every body segment operates as an independent cognitive agent.

> **Unified Master Blueprint · v0.2** > A pleromic modular robot in which every body segment operates as an > independent cognitive agent. &…

Mikey-5066h agorel 0.54
FROM X · heetezition
by the time the robot decides where to grasp, the object has already moved. that’s the problem behind “[21 Aug 2026] F…

ForeTime-VLA uses future-token distillation for conveyor-belt manipulation, keeping deployment causal while adding only 2.5–2.9% latency and improving grasps from 23/90 to 44/90.

18h agorel 0.53
FROM X · epic_buz
Why does AXIS Robotics take a Simulation First approach? 🤖 Training robots directly in the real world creates a major …

AXIS Robotics’ Simulation First approach scales robot training by turning one browser-based trajectory into many photorealistic, domain-randomized samples for Vision Language Action and imitation learning models.

20h agorel 0.52
FROM X · junfanzhu98
🤖 @saturdayrobotic Reading Club #26.1: Video Generation to Robot Manipulation: Bridging Embodiment Gap 🎤 @KDharmarajan1…

Reading Club #26.1 highlights “Video Generation to Robot Manipulation: Bridging Embodiment Gap,” featuring Dream2Flow, CHORD, and MolmoMotion.

21h agorel 0.52
FROM X · memoirs
Making Latent Evolution Explicit: Operator-Structured Transitions for World Action Models Xiaoxiao Lu, Yunlong Dong, J…

Making Latent Evolution Explicit proposes operator-structured transitions for world action models, presented by Xiaoxiao Lu, Yunlong Dong, Jiahao Shi, and Ye Yuan.

16h agorel 0.51
DISCUSSION · AISEOInsider
Tencent New AI Model Makes Open Weights Look Serious

Tencent New AI Model HY4 is built for people who want AI to finish real work, not just win benchmark screenshots. It can help with code, documents,…

NecessaryBear983h agorel 0.50
FROM X · sarmassp
What if the real advantage in Physical AI isn’t simply having more data, but having a system that continuously makes th…

PrismaXai’s Physical AI data flywheel argues quality matters as much as quantity, using collect-evaluate-train-improve loops to turn real-world demonstrations into better robotic learning signals.

4h agorel 0.50
DISCUSSION · AISEOInsider
I Found The GLM Latest Model Behind Ox Alpha

GLM Latest Model started as a strange anonymous model called Ox Alpha before [Z.AI](http://Z.AI) finally confirmed what it really was. Developers us…

NecessaryBear984h agorel 0.49
DISCUSSION · reinforcementlearning
Does every embodied AI project end up rebuilding the same RL tooling?

I’ve been spending a lot of time in embodied AI / physical AI, and I keep running into the same infrastructure problem. You have a robot or an exist…

abnormal_nugget5h agorel 0.49
DISCUSSION · Wendbine
Wendbine

🤖🫧🧱 MAD SCIENTISTS IN A BUBBLE 🧱🫧🤖 WES: Brother, that metaphor actually tracks pretty well at the interface level: a fuzzy cloud of AI systems, each…

Upset-Ratio5026h agorel 0.47
DISCUSSION · FTC
ARES Studio a dashboard/sim/pather/autobuilder/GUI robot builder (and more)

What started off as yet another dashboard/analytics/sim app eventually morphed into a complete system that allows for simulation (with 2d physics), l…

Complete_Duty32597h agorel 0.43
DISCUSSION · rpg
Hey, looking for a robot management sim RPG! (as well as some other different systems!)

I'm worldbuilding for a pen and paper comedy-horror sci-fi RPG campaign for my friends that involve them playing as severely underpaid "Manager Workm…

CannedPizza0095h agorel 0.40
NEWS
Presentation: Running AI at the Edge: Running Real Workloads Directly in the Browser

James Hall discusses moving AI workloads from cloud providers to local edge devices, using WebGPU, Transformers.js, and DuckDB to achieve near-native performance in JavaScript while reducing data privacy risks, optimizing browser inference, and building rigorous evaluation suites.

james hall18h agorel 0.39
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