# AdamNX: An Adam improvement algorithm based on a novel exponential decay mechanism for the second-order moment estimate

Source: [AdamNX: An Adam improvement algorithm based on a novel exponential decay mechanism for the second-order moment estimate](<https://www.sota2.com/research/paper/691bfe4e6750be83fe5cf082>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-07-28T05:00:05.261Z

Authors: Meng Zhu, Quan Xiao, Weidong Min

Published: 2025-11-17T15:07:55.000Z

## Abstract

This paper studies the exponential decay mechanism of the second-moment estimate in Adam. We propose AdamNX and a time-varying second-moment decay rate that gradually weakens the correction applied to the update scale. Under the assumptions used in our analysis, this mechanism makes the updates approach momentum-SGD-like behavior during the training plateau phase. We report results on the image-classification, object-detection, and semantic-segmentation tasks, configurations, and comparators included in this paper. These results do not establish multi-seed statistical effects, flatness, or generalization beyond the reported tasks. Our code is open-sourced at https://github.com/mengzhu0308/AdamNX.

## Recorded benchmark results

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## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2511.13465>)

[PDF](<https://arxiv.org/pdf/2511.13465.pdf>)