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Celebrity beauty files: K-beauty star Irene Kim says one skincare treatment has been her secret for 13 years
Celebrity beauty files: K-beauty star Irene Kim says one skincare treatment has been her secret for 13 years South Korea’s It girl talks beauty and how her skin journey has changed over the years. From fashion runways and global brand partnerships with Estee Lauder, Calvin Klein and Chanel to television hosting and entrepreneurship, Irene Kim remains one of Korea’s most influential beauty and fashion figures. Her latest venture is Skit, a skincare brand built around simplicity, emotion and...
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Almost balanced ordered biclique covering of graphs
arXiv:2606.08506v1 Announce Type: cross Abstract: Let $f(n,k)$ be the minimum size of a collection of bicliques such that (i) every edge of the complete graph $K_n$ is covered by at least one and at most $k$ bicliques in the collection, and (ii) for each edge $\{u,v\}$, the number of bicliques in which $u$ appears in the first class and $v$ in the second class differs by at most one from the number of bicliques in which $u$ appears in the second class and $v$ in the first class. For $k=1$,...
Beyond Augmented-Action Surrogates for Multi-Expert Learning-to-Defer
arXiv:2604.09414v5 Announce Type: replace-cross Abstract: A learning-to-defer (L2D) system decides, for each input, whether to predict on its own or to hand it to one of several available experts. The very well established recipe trains classifier and router jointly by treating the $K$ classes and $J$ experts as competing actions in one shared $(K{+}J)$-action geometry. Subsequent work has proposed a series of incremental fixes within this geometry; we show that each still suffers, to...
Almost covering all the layers of hypercube with multiplicities
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Resolving Ambiguity in Composed Image Retrieval via Calibrated Interaction
arXiv:2605.24634v3 Announce Type: replace Abstract: Composed image retrieval (CIR) searches a corpus with a reference image and a text describing how to modify it. Despite rapid progress from triplet-trained compositors to zero-shot and generative methods, essentially all systems share one assumption: that a query maps to a single target, scored by Recall@K against one annotation. We argue this is fundamentally at odds with the task.
$O(n +f(k))$: Truly Linear FPT
Announce Type: new Abstract: Parameterized complexity has always been concerned with practical computing: by confining combinatorial explosion to a secondary parameter $k$, one can uncover why and how many NP-hard problems are effectively tackled in practice. Today, however, the scale of data has changed: scientists study Big Data, which is so large that even quadratic dependence in the total input size $n$ is unaffordable. Therefore, what constitutes a practical algorithm has also changed.
The price of incrementality in k-center clustering
arXiv:2606.08713v1 Announce Type: new Abstract: The $k$-center problem is one of the best-studied and most intuitive clustering formulations. It asks, given a set of $n$ points in a metric space, for $k$ of the points to be designated as cluster centers, so that the maximum distance of an input point to its nearest center is minimized.
The anti-lexicographic SUS-anchor: a near-optimal k=1 sampling scheme
Announce Type: new Abstract: In recent years, there has been a renewed interest in the search for low density minimizer schemes. These schemes take a window of $w$ consecutive $k$-mers, and sample one of them: the smallest under some specific order. Schemes such as the mod-minimizer provide a low density (fraction of sampled $k$-mers) when $k \gg w$, while schemes such as the greedy minimizer work well for explicit small parameters roughly in the regime $k \leq 2w$, for $k$ and $w$ up to...
The anti-lexicographic SUS-anchor: a near-optimal k=1 sampling scheme
arXiv:2606.01190v2 Announce Type: replace Abstract: In recent years, there has been a renewed interest in the search for low density minimizer schemes. These schemes take a window of $w$ consecutive $k$-mers, and sample one of them: the smallest under some specific order. Schemes such as the mod-minimizer provide a low density (fraction of sampled $k$-mers) when $k \gg w$, while schemes such as the greedy minimizer work well for explicit small parameters roughly in the regime $k \leq 2w$,...