pith:FJ5ZTZMR
PrecisionCUA: Iterative Visual Refinement for Pixel-Precise Cursor Grounding in Code Editors
Multi-turn refinement using visual feedback from prior attempts achieves higher click precision and task success in GUI grounding for dense coding interfaces than single-shot prediction.
arxiv:2604.13019 v2 · 2026-04-14 · cs.CV
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Record completeness
Claims
multi-turn refinement significantly outperforms state-of-the-art single-shot models in both click precision and overall task success rate.
That models can reliably interpret and act on visual feedback from prior attempts to self-correct without introducing additional errors or failing to adapt to dynamic UI changes.
Multi-turn visual feedback refinement outperforms single-shot coordinate prediction for pixel-precise GUI grounding in complex coding environments.
Receipt and verification
| First computed | 2026-05-28T01:04:40.028897Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
2a7b99e591d8ceb04f597ff07bb5291a8861d27706eb51220b14861b30569845
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/FJ5ZTZMR3DHLAT2ZP7YHXNJJDK \
| 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: 2a7b99e591d8ceb04f597ff07bb5291a8861d27706eb51220b14861b30569845
Canonical record JSON
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