Negation-Aware Weighted Information Fusion for Reliable Evidential Reasoning

arXiv:2509.00754 · cs.LG · Submitted 2025-08-31 · Read on arXiv

cs.LG

Submitted: 2025-08-31

Updated: 2026-09-19

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

Accuracy — 37× in this paper · explained in 1 episode
Benchmark — 7× in this paper · explained in 2 episodes
K-Nearest Neighbor — 7× in this paper
Basic Probability Assignment — 5× in this paper
Dempster-Shafer Theory — 5× in this paper
Gaussian Mixture Model — 5× in this paper
Ablation — 3× in this paper · explained in 1 episode
Few-Shot Learning — 3× in this paper · explained in 4 episodes
Ablation Studies — 2× in this paper · explained in 1 episode
Calibration — 2× in this paper · explained in 7 episodes
Clustering — 2× in this paper · explained in 2 episodes
Gaussian Mixture Model (GMM) — 2× in this paper · explained in 2 episodes
Generalization — 2× in this paper · explained in 13 episodes
Naive Bayes — 2× in this paper
Negation-Aware Weighted Information Fusion — 2× in this paper
Random Forest — 2× in this paper
Robustness — 2× in this paper · explained in 5 episodes
Active Learning — 1× in this paper · explained in 6 episodes
Adaptation — 1× in this paper · explained in 1 episode
Bayesian Inference — 1× in this paper · explained in 5 episodes
Cooperation — 1× in this paper · explained in 2 episodes
Core — 1× in this paper · explained in 2 episodes
Domain Adaptation — 1× in this paper · explained in 5 episodes
Transfer Learning — 1× in this paper · explained in 10 episodes
Transformer — 1× in this paper · explained in 2 episodes

Sources

A Closer Look at Few-shot Classification

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