Pith Number

pith:GNQPJI4S

pith:2025:GNQPJI4STITBXFP7ZUCQA7D4F7

not attested not anchored not stored refs resolved

Genie Envisioner: A Unified World Foundation Platform for Robotic Manipulation

Donglin Yang, Guanghui Ren, Jianlan Luo, Jingbin Cai, Liliang Chen, Maoqing Yao, Pengfei Zhou, Shengcong Chen, Shuicheng Yan, Si Liu, Siyuan Huang, Yue Hu, Yue Liao, Yuxin Jiang

A single instruction-conditioned video diffusion model unifies policy learning, simulation, and evaluation for robotic manipulation.

arxiv:2508.05635 v3 · 2025-08-07 · cs.RO · cs.CV

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?

Add to your LaTeX paper

\usepackage{pith}
\pithnumber{GNQPJI4STITBXFP7ZUCQA7D4F7}

Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge

Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

GE integrates policy learning, evaluation, and simulation within a single video-generative framework, establishing a scalable and practical foundation for instruction-driven, general-purpose embodied intelligence.

C2weakest assumption

That the instruction-conditioned video diffusion model in GE-Base sufficiently captures real-world spatial, temporal, and semantic dynamics to support accurate action mapping in GE-Act and reliable rollouts in GE-Sim across diverse embodiments.

C3one line summary

Genie Envisioner unifies robotic policy learning, simulation, and evaluation inside one instruction-conditioned video diffusion framework using GE-Base, GE-Act, and GE-Sim.

References

30 extracted · 30 resolved · 20 Pith anchors

[1] Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs · arXiv:2503.01743

[2] Cosmos World Foundation Model Platform for Physical AI · arXiv:2501.03575

[3] Do As I Can, Not As I Say: Grounding Language in Robotic Affordances · arXiv:2204.01691

[4] Qwen2.5-VL Technical Report · arXiv:2502.13923

[5] GR00T N1: An Open Foundation Model for Generalist Humanoid Robots · arXiv:2503.14734

Formal links

3 machine-checked theorem links

Cited by

25 papers in Pith

A Survey on Vision-Language-Action Models for Embodied AI

WorldArena 2.0: Extending Embodied World Model Benchmarking on Modality, Functionality and Platform

Key-Gram: Extensible World Knowledge for Embodied Manipulation

DriveLaW:Unifying Planning and Video Generation in a Latent Driving World

RISE: Self-Improving Robot Policy with Compositional World Model

Receipt and verification

First computed	2026-05-17T23:38:50.107568Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

3360f4a3929a261b95ffcd05007c7c2fdf99d14c8a47b913f375957d457a151f

Aliases

arxiv: 2508.05635 · arxiv_version: 2508.05635v3 · doi: 10.48550/arxiv.2508.05635 · pith_short_12: GNQPJI4STITB · pith_short_16: GNQPJI4STITBXFP7 · pith_short_8: GNQPJI4S

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/GNQPJI4STITBXFP7ZUCQA7D4F7 \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 3360f4a3929a261b95ffcd05007c7c2fdf99d14c8a47b913f375957d457a151f

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "97caad6ad19a11beb1bd896fc1d5c61e7b25d856f5a70d6c789693cb7c831960",
    "cross_cats_sorted": [
      "cs.CV"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.RO",
    "submitted_at": "2025-08-07T17:59:44Z",
    "title_canon_sha256": "5328146171b55d888e894fcfc9a7a0b678ebab9e88c800f3a863ca6e1cdc1e83"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2508.05635",
    "kind": "arxiv",
    "version": 3
  }
}