Pith Number

pith:2IFRYFVV

pith:2026:2IFRYFVV5LGFHEW7SOLZEBZ7IB

not attested not anchored not stored refs resolved

Before the Body Moves: Learning Anticipatory Joint Intent for Language-Conditioned Humanoid Control

Haozhe Jia, Honglei Jin, Jianfei Song, Kuimou Yu, Lei Wang, Shaofeng Liang, Shuxu Jin, Wenshuo Chen, Youcheng Fan, Yuan Zhang, Yutao Yue, Zinuo Zhang

DAJI learns dynamics-aligned joint intents so language commands produce humanoid actions that are both immediate and anticipatory of future contacts and balance shifts.

arxiv:2605.14417 v1 · 2026-05-14 · 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{2IFRYFVV5LGFHEW7SOLZEBZ7IB}

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

DAJI achieves strong results in anticipatory latent learning, single-instruction generation, and streaming instruction following, reaching 94.42% rollout success on HumanML3D-style generation and 0.152 subsequence FID on BABEL.

C2weakest assumption

That distilling a future-aware teacher policy into a deployable diffusion action policy via student-driven rollouts preserves the anticipatory properties without substantial degradation in closed-loop performance.

C3one line summary

DAJI learns future-aware joint intents from language to enable proactive humanoid control, reporting 94.42% rollout success on HumanML3D-style tasks and 0.152 subsequence FID on BABEL.

References

48 extracted · 48 resolved · 8 Pith anchors

[1] J.Massion,“Movement,postureandequilibrium:Interaction and coordination”,Progress in neurobiology, vol. 38, no. 1, pp.35–56,1992 1992

[2] S.BouissetandM.-C.Do,“Posture,dynamicstability,andvol- untarymovement”,NeurophysiologieClinique/ClinicalNeuro- physiology,vol.38,no.6,pp.345–362,2008 2008

[3] MuJoCo: A physics engine for model-based control 2012 · doi:10.1109/iros.2012.6386109

[4] The kit motion- languagedataset 2016

[5] Proximal Policy Optimization Algorithms 2017 · arXiv:1707.06347

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-17T23:39:07.290905Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

d20b1c16b5eacc5392df939792073f406609c58caea4f90ec68384b95a2c913d

Aliases

arxiv: 2605.14417 · arxiv_version: 2605.14417v1 · doi: 10.48550/arxiv.2605.14417 · pith_short_12: 2IFRYFVV5LGF · pith_short_16: 2IFRYFVV5LGFHEW7 · pith_short_8: 2IFRYFVV

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/2IFRYFVV5LGFHEW7SOLZEBZ7IB \
  | 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: d20b1c16b5eacc5392df939792073f406609c58caea4f90ec68384b95a2c913d

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "6288f1b1ae9c3eb8a08b65b33187f89b3afbae98dfac0c7893929907c4154a9e",
    "cross_cats_sorted": [
      "cs.CV"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.RO",
    "submitted_at": "2026-05-14T06:05:24Z",
    "title_canon_sha256": "aef4c6b08e86424c0911a15e05a0879f6faefb8e7ad3ce9f1d6ba3400abf6c73"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.14417",
    "kind": "arxiv",
    "version": 1
  }
}