Pith Number

pith:RMFFWE7M

pith:2026:RMFFWE7MLGWODXOIUHOITI3DX5

not attested not anchored not stored refs pending

Let Robots Feel Your Touch: Visuo-Tactile Cortical Alignment for Embodied Mirror Resonance

Anan Li, Guyue Zhou, Jiasi Gao, Ning An, Qingming Luo, Rui Wang, Tianfang Zhu

Mirror Touch Net aligns visual and tactile representations so robots can predict detailed touch sensations from RGB images.

arxiv:2605.14571 v1 · 2026-05-14 · cs.RO · cs.LG

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\pithnumber{RMFFWE7MLGWODXOIUHOITI3DX5}

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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

Mirror Touch Net imposes semantic, distributional and geometric alignment between visual and tactile representations through multi-level constraints, enabling prediction of millimetre-scale tactile signals across 1,140 taxels on a robotic hand from RGB images.

C2weakest assumption

That the imposed multi-level alignment constraints successfully instantiate the structural correspondence between visual and somatosensory cortices and that this produces genuine mirror resonance rather than a superficial mapping.

C3one line summary

Mirror Touch Net aligns visual and tactile data manifolds to predict millimetre-scale touch signals across 1,140 taxels from images, extending to human hand observations for reflexive robotic responses.

Formal links

1 machine-checked theorem link

Receipt and verification

First computed	2026-05-17T23:39:05.469983Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

8b0a5b13ec59ace1ddc8a1dc89a363bf73e4fb6ccde630b12e9654f68b6eb77d

Aliases

arxiv: 2605.14571 · arxiv_version: 2605.14571v1 · doi: 10.48550/arxiv.2605.14571 · pith_short_12: RMFFWE7MLGWO · pith_short_16: RMFFWE7MLGWODXOI · pith_short_8: RMFFWE7M

Agent API

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/RMFFWE7MLGWODXOIUHOITI3DX5 \
  | 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: 8b0a5b13ec59ace1ddc8a1dc89a363bf73e4fb6ccde630b12e9654f68b6eb77d

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "6d28eb95de3dcbb2fe353d96bf0b4f3c2c8ce913842d6563b037dd1c26680581",
    "cross_cats_sorted": [
      "cs.LG"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.RO",
    "submitted_at": "2026-05-14T08:40:24Z",
    "title_canon_sha256": "43f621d4509617bb9112e13b853c1e1986a85dacf73501999bc0006ee46f5ef3"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.14571",
    "kind": "arxiv",
    "version": 1
  }
}