Pith Number

pith:DCSODNAL

pith:2026:DCSODNALU54VPBZDS5MN2MAEVY

not attested not anchored not stored refs resolved

PhysBrain 1.0 Technical Report

Bin Yu, Changti Wu, Cong Huang, Haishan Liu, Hang Yuan, Kai Chen, Shijie Lian, Xiaolin Hu, Xiaopeng Lin, Yukun Shi, Yuxuan Tian, Yuzhuo Miao, Zhaolong Shen

Human egocentric video supplies physical commonsense that boosts robot policy performance to state-of-the-art levels.

arxiv:2605.15298 v1 · 2026-05-14 · cs.RO · cs.AI · cs.CL · cs.CV

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\pithnumber{DCSODNALU54VPBZDS5MN2MAEVY}

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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

Across multimodal QA benchmarks and embodied control benchmarks, including ERQA, PhysBench, SimplerEnv-WidowX, LIBERO, and RoboCasa, PhysBrain 1.0 achieves SOTA results and shows especially strong out-of-domain performance on SimplerEnv.

C2weakest assumption

The data engine accurately extracts scene elements, spatial dynamics, action execution, and depth-aware relations from human egocentric video in a form that produces effective physical commonsense supervision transferable to robot policies.

C3one line summary

PhysBrain 1.0 extracts scene elements, spatial dynamics, actions and depth relations from human egocentric video to create QA supervision for VLMs, then transfers the resulting physical priors to VLA policies via capability-preserving adaptation.

References

45 extracted · 45 resolved · 16 Pith anchors

[1] I. Apanasevich, M. Artemyev, R. Babakyan, P. Fedotova, D. Grankin, E. Kupryashin, A. Misailidi, D. Nerus, A. Nutalapati, G. Sidorov, I. Efremov, M. Gerasyov, D. Pikurov, Y. Senchenko, S. Davidenko, D. 2026

[2] Qwen3-VL Technical Report 2025 · arXiv:2511.21631

[3] GR00T N1: An Open Foundation Model for Generalist Humanoid Robots 2025 · arXiv:2503.14734

[4] $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control 2024 · arXiv:2410.24164

[5] BuildAI. Egocentric-10k, 2025. URLhttps://huggingface.co/datasets/builddotai/Egocentric-10K 2025

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-20T00:00:51.334069Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

18a4e1b40ba7795787239758dd3004ae3cc9b93d8b87ec1cb993dc5a4c4069ec

Aliases

arxiv: 2605.15298 · arxiv_version: 2605.15298v1 · doi: 10.48550/arxiv.2605.15298 · pith_short_12: DCSODNALU54V · pith_short_16: DCSODNALU54VPBZD · pith_short_8: DCSODNAL

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/DCSODNALU54VPBZDS5MN2MAEVY \
  | 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: 18a4e1b40ba7795787239758dd3004ae3cc9b93d8b87ec1cb993dc5a4c4069ec

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "9293d7fa243c48d542ad5e009febcdbbb9e4ed66f36bf136c8100bf7593a774e",
    "cross_cats_sorted": [
      "cs.AI",
      "cs.CL",
      "cs.CV"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.RO",
    "submitted_at": "2026-05-14T18:11:47Z",
    "title_canon_sha256": "71ba1633d074b402af6a19df2396d11721fb4c3dbf156a7eba78a58241d4ec03"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.15298",
    "kind": "arxiv",
    "version": 1
  }
}