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Evidence record 14837 · automatically gathered

Directional Influence Function: Estimating Training Data Influence in Constrained Learning

As constrained learning becomes increasingly common, models are trained under explicit feasibility requirements to enforce fairness, safety, robustness, regulariza- tion, and physics or logic constraints. Understanding how training samples in- fluence the model solution (e.g., learned parameters) is crucial for interpretability and robustness. The classical influence function (IF) estimates sample contribu- tions via local sensitivity analysis, measuring how the solution changes when a specific

Record details

Published: 25 July 2026
Source: arXiv fairness query
Category: Research
Topics: Bias & fairness · Safety & alignment
Retrieved: 30 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

Same publisher byline · Shared topic: Bias & fairness

Directional Influence Function: Estimating Training Data Influence in Constrained Learning

arXiv fairness query · 25 July 2026

Shared topic: Bias & fairness · Shared topic: Safety & alignment

Unsupervised Graph Representation Learning with Complementary View Alignment

arXiv cs.LG · 27 July 2026

Shared topic: Bias & fairness · Shared topic: Safety & alignment

Shape-Based Inductive Bias for Glioma Grading from Tumor Contours

arXiv cs.LG · 27 July 2026

Shared topic: Bias & fairness · Shared topic: Safety & alignment

Spectral Prior for Reducing Exposure Bias in Diffusion Models

HuggingFace Daily Papers · 23 July 2026

Shared topic: Bias & fairness · Shared topic: Safety & alignment

Language Models Embody and Amplify Human Cognitive Distortions: What Is to Be Done?

arXiv · 22 July 2026

Shared topic: Bias & fairness · Shared topic: Safety & alignment

PG-KINN: A Physics-Informed Petrov-Galerkin Kolmogorov-Arnold Network for Solving Forward and Inverse PDEs

arXiv cs.LG · 22 July 2026

How to cite this record

ethics.ai (25 July 2026), “Directional Influence Function: Estimating Training Data Influence in Constrained Learning,” evidence record 14837, https://ethics.ai/record/14837 (originally published by arXiv fairness query).

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