PulseAugur
EN
LIVE 19:05:02

Researchers Fix Numerical Bugs in Softmax and Cross-Entropy Implementations

Researchers have identified and fixed two numerical bugs in standard implementations of softmax, log-softmax, and cross-entropy. The first bug, Softmax Collapse, causes the target logit's gradient to round to zero when one logit is significantly larger than others, disrupting the gradient sum. The second bug, Softmax Cancellation, produces non-zero gradients even when student and teacher logits are identical, occurring when these logits are close. The proposed solutions eliminate the "Slingshot" phenomenon, accelerate grokking with weight decay, and prevent accuracy collapse without it. AI

IMPACT Fixes may improve training stability and efficiency for models using these common functions.

RANK_REASON The cluster contains an academic paper detailing a technical fix for common machine learning functions. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Researchers Fix Numerical Bugs in Softmax and Cross-Entropy Implementations

How we ranked this

Signal score
4 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
The cluster contains an academic paper detailing a technical fix for common machine learning functions. [lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
paper, other
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
Same-day
Cluster formed today. Ranking reflects the current source set at time of score.

Full methodology in our editorial standards.

COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Jonathan T. Barron, Dan Gnanapragasam, Michael Tschannen ·

    A Fix for Softmax and Cross-Entropy

    arXiv:2610.31642v1 Announce Type: new Abstract: Standard implementations of softmax, log-softmax, and cross-entropy have two numerical bugs. The first bug, Softmax Collapse, rounds the target logit's gradient to zero if that one logit is much larger than the others, resulting in …