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Wiola is a novel Small Language Model architecture introducing five independently designed components—SRPE, GCLA, ATM, DSFF, and WiolaRMSNorm—aimed at improving efficiency and coherence, released in sizes from 120M to 1.5B parameters and integrated with HuggingFace Transformers.
This document discusses the challenges of Unicode filename composition (NFC vs NFD) across different operating systems in the context of the Subversion version control system, and proposes solutions for handling these differences.
This paper proposes TOPSIS-RAD, a modified version of the TOPSIS method that incorporates decision-maker-defined reference levels (VPL and DPL) to address issues like misalignment with preferences, outlier sensitivity, and rank reversal.
The article compares two methods for normalizing RGB values (dividing by 255 vs 256) and explains the consequences for floating-point conversion and rounding, including uneven bin widths at the extremes.
This paper systematically studies scale vectors in LLM normalization layers, showing they optimize training through a self-amplifying preconditioning effect, and proposes three lightweight improvements that enhance performance and scaling behavior with negligible overhead.
This paper introduces a new energy-based model for linear inverse problems that learns normalized posterior densities, overcoming limitations of diffusion models. It enables unbiased sampling, adaptive sampling, and blind degradation estimation, with competitive performance on ImageNet, CelebA, and AFHQ.
The article reframes columnar storage as an extreme form of database normalization, showing how splitting attributes into position-aligned arrays mirrors normalized tables joined on an implicit ordinal primary key.