Pith Number

pith:GRQAVAUJ

pith:2026:GRQAVAUJLHOLHOYGN5NYY5B7K6

not attested not anchored not stored refs pending

Learning Human-Intention Priors from Large-Scale Human Demonstrations for Robotic Manipulation

Guangyu Chen, Jinkun Liu, Wenbo Ding, Yifan Xie, Yuan Wang, Yu Sun

MoT-HRA learns human-intention priors from 2.2 million video episodes to guide more reliable robot manipulation.

arxiv:2604.24681 v2 · 2026-04-27 · cs.RO

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\usepackage{pith}
\pithnumber{GRQAVAUJLHOLHOYGN5NYY5B7K6}

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Record completeness

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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

Experiments on hand motion generation, simulated manipulation, and real-world robot tasks show that MoT-HRA improves motion plausibility and robust control under distribution shift.

C2weakest assumption

The hand-centric filtering, spatial reconstruction, temporal segmentation, and language alignment steps used to curate HA-2.2M from heterogeneous human videos successfully extract embodiment-agnostic human-intention priors without introducing substantial artifacts, biases, or loss of critical information.

C3one line summary

MoT-HRA learns embodiment-agnostic human-intention priors from the HA-2.2M dataset of 2.2M human video episodes through a three-expert hierarchy to improve robotic motion plausibility and robustness under distribution shift.

Receipt and verification

First computed	2026-05-22T01:04:03.266172Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

34600a828959dcb3bb066f5b8c743f57be7943b8efc14c3b1da63586ce3bd91e

Aliases

arxiv: 2604.24681 · arxiv_version: 2604.24681v2 · doi: 10.48550/arxiv.2604.24681 · pith_short_12: GRQAVAUJLHOL · pith_short_16: GRQAVAUJLHOLHOYG · pith_short_8: GRQAVAUJ

Agent API

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/GRQAVAUJLHOLHOYGN5NYY5B7K6 \
  | 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: 34600a828959dcb3bb066f5b8c743f57be7943b8efc14c3b1da63586ce3bd91e

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "9a7bfcc568bc41266cd16956e666af7770068d98376afd8fd735c12302fd09d8",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.RO",
    "submitted_at": "2026-04-27T16:42:18Z",
    "title_canon_sha256": "63f2c3e9f6d365c198ae85a9197536e4ade200b0bfd8ad0a6d5a8cea836f2db4"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.24681",
    "kind": "arxiv",
    "version": 2
  }
}