pith:ZYNQQBUH
LVLMs and Humans Ground Differently in Referential Communication
Large vision-language models cannot interactively generate and resolve referring expressions to build common ground with humans or each other.
arxiv:2601.19792 v5 · 2026-01-27 · cs.CL · cs.AI · cs.HC
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\usepackage{pith}
\pithnumber{ZYNQQBUHQD4GJSR4TUL3MMNKNK}
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Claims
We show that LVLMs cannot interactively generate and resolve referring expressions in a way that enables smooth communication, a crucial skill that underlies human language use.
The assumption that performance differences in this specific non-lexicalized object matching task directly reflect broader deficits in LVLMs' ability to model common ground in general communication.
LVLMs and humans build common ground differently in referential tasks, with LVLMs failing to enable smooth interactive communication in a new corpus of 356 dialogues.
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| First computed | 2026-06-19T16:12:05.435088Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
ce1b08068780f864ca3c9d17b631aa6aa8c019a8e715e18662b461f1aff410f5
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· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/ZYNQQBUHQD4GJSR4TUL3MMNKNK \
| 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: ce1b08068780f864ca3c9d17b631aa6aa8c019a8e715e18662b461f1aff410f5
Canonical record JSON
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