pith:JY4XZCER
DSH-Bench: A Difficulty- and Scenario-Aware Benchmark with Hierarchical Subject Taxonomy for Subject-Driven Text-to-Image Generation
DSH-Bench supplies a hierarchical taxonomy and difficulty-scenario labels to expose where subject-driven text-to-image models lose identity.
arxiv:2603.08090 v3 · 2026-03-09 · cs.CV · cs.AI
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Claims
DSH-Bench enables systematic multi-perspective analysis of subject-driven T2I models through four principal innovations: hierarchical taxonomy sampling, difficulty and scenario classification, the SICS metric with 9.4% higher human correlation, and diagnostic insights for model optimization.
The assumption that the chosen hierarchical taxonomy and difficulty/scenario labels are sufficiently comprehensive and unbiased, and that the reported 9.4% correlation improvement for SICS generalizes beyond the specific human evaluators and model set used in the study.
DSH-Bench is a benchmark for subject-driven T2I generation that uses hierarchical taxonomy sampling, difficulty/scenario classification, and a new SICS metric showing 9.4% higher human correlation than prior measures.
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| First computed | 2026-07-01T01:17:13.897447Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
4e397c889107160cc803b47459ffad6887bc814bd3593be5850ee0d64fc9745d
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/JY4XZCERA4LAZSADWR2FT75NNC \
| 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: 4e397c889107160cc803b47459ffad6887bc814bd3593be5850ee0d64fc9745d
Canonical record JSON
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