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pith:E6XBFBWF

pith:2026:E6XBFBWFCQUWDNKRCVRJAMMBBD
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Embodied Interpretability: Linking Causal Understanding to Generalization in Vision-Language-Action Models

Abdulqader Dhafer, Hanxin Zhang, Hongbiao Dong, Mingshuo Xu, Shigang Yue, Zhou Daniel Hao

Interventional attribution reveals when vision-language-action models depend on spurious features rather than true causes.

arxiv:2605.00321 v2 · 2026-05-01 · cs.RO

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Claims

C1strongest claim

Experiments across diverse manipulation tasks indicate that NMR predicts generalization behavior and that ISS yields more faithful explanations than existing interpretability methods.

C2weakest assumption

That the interventional masking procedure yields unbiased estimates of causal influence on actions and that action prediction error serves as a valid proxy for causal influence under the characterized conditions.

C3one line summary

Interventional attribution via ISS and NMR diagnoses causal misalignment in VLA policies and predicts their generalization performance across manipulation tasks.

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1 paper in Pith

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First computed 2026-06-11T01:10:36.917482Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

27ae1286c5142961b551156290318108dfeab7749a840984e81ec33ff8f968f8

Aliases

arxiv: 2605.00321 · arxiv_version: 2605.00321v2 · doi: 10.48550/arxiv.2605.00321 · pith_short_12: E6XBFBWFCQUW · pith_short_16: E6XBFBWFCQUWDNKR · pith_short_8: E6XBFBWF
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/E6XBFBWFCQUWDNKRCVRJAMMBBD \
  | 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: 27ae1286c5142961b551156290318108dfeab7749a840984e81ec33ff8f968f8
Canonical record JSON
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    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.RO",
    "submitted_at": "2026-05-01T01:00:00Z",
    "title_canon_sha256": "080ec0cf66f20199d1138b95e1bb171f2aa0d7f25eb19d8f5c889318352be54e"
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