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DEPICT: Scoring Text-to-Image Alignment by Answer Agreement

Paper recorded by Signals 4 on 2026-10-02 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-02 on arXiv · recorded by Signals 4 on 2026-10-05

Category: cs.CV · 计算机视觉 · first seen 2026-10-05

Abstract

Image-text alignment is a core problem in computer vision with applications in caption evaluation, hallucination detection, data curation, and the benchmarking of text-to-image (T2I) generators. As T2I models improve, benchmarking has become demanding, requiring metrics capable of finding a series of issues like missing objects, swapped attributes, miscounts, and ignored negations. Recent work add

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#370 most recent of 756 cs.CV papers we have recorded · ↑ newer: ProAR: Learning Prospective Reasoning with Autoregressive Video Models · ↓ older: ManifoldSplat: Language-Guided Semantic Shape Editing of 3D Gaussian H
Cite this page: DEPICT: Scoring Text-to-Image Alignment by Answer Agreement: the #370 most recent of 756 cs.CV papers we have recorded (as of 2026-10-02). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/depict-scoring-text-to-image-alignment-by-answer-agreement.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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