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pith:2026:X6SQH5VVKARAFFARJOYYKTMMB4
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Does Theory of Mind Improvement Really Benefit Human-AI Interactions? Empirical Findings from Interactive Evaluations

Haotian Li, Huamin Qu, Jianxun Lian, Nanxu Gong, Xing Xie, Yanjie Fu, Zishu Zhao, Zixin Chen

Theory of Mind gains on static benchmarks often fail to improve performance in live human-AI interactions.

arxiv:2605.15205 v1 · 2026-04-28 · cs.AI

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Claims

C1strongest claim

Improvements on static benchmarks do not always translate to better performance in dynamic HAI interactions.

C2weakest assumption

The chosen interactive tasks and user-study protocol sufficiently represent the first-person, dynamic, open-ended nature of typical human-AI interactions (section on paradigm shift and evaluation setup).

C3one line summary

Improvements in LLM Theory of Mind on static benchmarks do not reliably improve performance in dynamic, first-person human-AI interactions across goal-oriented and experience-oriented tasks.

References

63 extracted · 63 resolved · 1 Pith anchors

[1] Aho and Jeffrey D 1972
[2] Publications Manual , year = "1983", publisher = 1983
[3] Chandra and Dexter C 1981 · doi:10.1145/322234.322243
[4] Scalable training of
[5] Dan Gusfield , title =. 1997 1997
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First computed 2026-05-20T00:00:45.990531Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

bfa503f6b550220294114bb1854d8c0f29b113f40174ed4eb8bde91362a39616

Aliases

arxiv: 2605.15205 · arxiv_version: 2605.15205v1 · doi: 10.48550/arxiv.2605.15205 · pith_short_12: X6SQH5VVKARA · pith_short_16: X6SQH5VVKARAFFAR · pith_short_8: X6SQH5VV
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/X6SQH5VVKARAFFARJOYYKTMMB4 \
  | 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())"
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Canonical record JSON
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