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a23acdf db295a6 a23acdf | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | <p>Ordered roughly by expected value for the research question.</p>
<ol>
<li><strong>Uncertainty in the numbers themselves.</strong> Repeated grouped splits with paired ablations are implemented
(<code>scripts/evaluate_multisplit.py</code>); show them on the website's Experiments page as well, and extend them to the
collection-disjoint experiments.</li>
<li><strong>More institutions.</strong> The Art Institute of Chicago (its API was blocked for programmatic clients during development;
its CC0 data dump is an alternative), the Rijksmuseum, the Smithsonian Open Access, Europeana providers with explicit
CC0/PDM rights. More institutions make collection-disjoint evaluation far more informative.</li>
<li><strong>Better out-of-distribution evaluation.</strong> A held-out set of non-paintings (sculpture, photographs, prints) and of
traditions absent from training, to measure the abstention and out-of-scope rules directly.</li>
<li><strong>Representation comparisons.</strong> Fine-tuned DINOv2 (linear-probe vs. partial fine-tuning with grouped cross-validation),
other self-supervised encoders, multi-crop or tiled embeddings for extreme aspect ratios (handscrolls).</li>
<li><strong>Ordinal and range-aware period models.</strong> Ordinal regression or interval-censored losses that use date ranges directly
instead of discarding works that span several bins.</li>
<li><strong>Hierarchical modelling.</strong> Joint region–tradition models; conformal prediction sets ("one of these two regions")
instead of a single abstention threshold.</li>
<li><strong>Explanations that are actually computed.</strong> Patch-level similarity maps between an upload and its nearest neighbours
(DINOv2 patch tokens), shown as evidence of <em>where</em> images are similar — with the caveat that similarity is not
reasoning.</li>
<li><strong>Other media.</strong> Prints, textiles, ceramics, sculpture — each with its own photographic conventions and evaluation.</li>
<li><strong>Curator-in-the-loop review.</strong> A reviewed sample of region mappings and failure cases (see annotation_protocol.md)
to estimate label noise.</li>
</ol> |