Pith Number

pith:Z3GWZ76I

pith:2026:Z3GWZ76ILF57NR6EZVDLG5GLCQ

not attested not anchored not stored refs resolved

Artificial Intelligence can Recognize Whether a Job Applicant is Selling and/or Lying According to Facial Expressions and Head Movements Much More Correctly Than Human Interviewers

Che-Wei Liu, Han-Chih Fan, Hung-Yue Suen, Kuo-En Hung, Yu-Sheng Su

Deep learning models detect honest and deceptive impression management in job interviews from facial expressions and head movements more accurately than human interviewers.

arxiv:2605.17461 v1 · 2026-05-17 · cs.HC · cs.AI · cs.CY

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\pithnumber{Z3GWZ76ILF57NR6EZVDLG5GLCQ}

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2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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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

Our models explained 91% and 84% of the variance in honest and deceptive IMs, respectively, and showed stronger correlations with self-reported IM scores than human interviewers.

C2weakest assumption

Self-reported IM measures from post-interview surveys serve as accurate and unbiased ground truth for both training the models and evaluating their performance against human interviewers.

C3one line summary

Deep learning models analyzing temporal facial expressions and head movements in interview videos explained 91% and 84% of variance in self-reported honest and deceptive impression management, outperforming human interviewers' correlations with the same self-reports.

References

73 extracted · 73 resolved · 1 Pith anchors

[1] Initial impressions: What they are, what they are not, and how they influence structured interview outcomes, 2016 · doi:10.1037/apl0000077

[2] Why does impression management positively influence interview ratings? The mediating role of competence and warmth, 2019 · doi:10.1111/ijsa.12260

[3] ‘Faking’ from the applicant's perspective: A theory of self - presentation in personnel selection settings, 2009 · doi:10.1111/j.1468

[4] “I (might be) just that good 2018 · doi:10.1111/peps.12285

[5] Honest and deceptive impression management in the employment interview: Can it be detected and how does it impact evaluations?, 2015 · doi:10.1111/peps.12079

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-20T00:04:40.208119Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

cecd6cffc8597bf6c7c4cd46b374cb140fb73e5b2786943306864445575bde95

Aliases

arxiv: 2605.17461 · arxiv_version: 2605.17461v1 · doi: 10.48550/arxiv.2605.17461 · pith_short_12: Z3GWZ76ILF57 · pith_short_16: Z3GWZ76ILF57NR6E · pith_short_8: Z3GWZ76I

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/Z3GWZ76ILF57NR6EZVDLG5GLCQ \
  | 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: cecd6cffc8597bf6c7c4cd46b374cb140fb73e5b2786943306864445575bde95

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "4e36ce79984185c37b837ab91d9d3f7eceb9a3c478d496c5666c3022be44426d",
    "cross_cats_sorted": [
      "cs.AI",
      "cs.CY"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.HC",
    "submitted_at": "2026-05-17T14:03:08Z",
    "title_canon_sha256": "1e58e455e760ab9b060b9af6043dd9fccaa8d11762d0d9730a5d9f99259d4e4c"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.17461",
    "kind": "arxiv",
    "version": 1
  }
}