CybAI news

[Submitted on 3 Feb 2022 (v1), last revised 23 Jan 2025 (this version, v2)] View a PDF of the paper titled Ranking with Confidence for Large Scale Comparison Data, by Filipa Valdeira and 1 other authors View PDF HTML (experimental) Abstract:In this work, we leverage a generative data model considering comparison noise to develop a fast, precise, and informative ranking algorithm from pairwise comparisons that produces a measure of confidence on each comparison. The problem of ranking a large number of items from noisy and sparse pairwise comparison data arises in diverse applications, like ranking players in online games, document…

arXiv:2501.13353v1 Announce Type: new Abstract: Transformers have become increasingly popular for image super-resolution (SR) tasks due to their strong global context modeling capabilities. However, their quadratic computational complexity necessitates the use of window-based attention mechanisms, which restricts the receptive field and limits effective context expansion. Recently, the Mamba architecture has emerged as a promising alternative with linear computational complexity, allowing it to avoid window mechanisms and maintain a large receptive field. Nevertheless, Mamba faces challenges in handling long-context dependencies when high pixel-level precision is required, as in SR tasks. This is due to its hidden state mechanism, which can compress…

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