A 2x2 factorial experiment on Qwen3.5-4B shows that relational structure and first-person register interact to drive behavioral persistence after functional collapse, while attention tracks lexical surprise and emotion probes track structure alone.
Hebbian learning with gradients: Hebbian convolutional neural networks with modern deep learning frameworks.arXiv preprint arXiv:2107.01729, 2021
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
HCL-FF augments the Forward-Forward algorithm with hierarchical learning and contrastive objectives to reach new state-of-the-art accuracies among FF methods on CIFAR-10 (+5.46%), CIFAR-100 (+17.00%), and Tiny-ImageNet (+12.51%).
citing papers explorer
-
Relational Intervention During Functional Collapse in Large Language Models: A Lexical-Statistical Ablation and a Structure x Register Factorial
A 2x2 factorial experiment on Qwen3.5-4B shows that relational structure and first-person register interact to drive behavioral persistence after functional collapse, while attention tracks lexical surprise and emotion probes track structure alone.