Pytorch implementation of a simple way to enable (Stochastic) Frame Averaging for any network
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Updated
Jul 26, 2024 - Python
Pytorch implementation of a simple way to enable (Stochastic) Frame Averaging for any network
Layer-wise Semantic Dynamics (LSD) is a model-agnostic framework for hallucination detection in Large Language Models (LLMs). It analyzes the geometric evolution of hidden-state semantics across transformer layers, using contrastive alignment between model activations and ground-truth embeddings to detect factual drift and semantic inconsistency.
A geometric k-simplex lattice-based vocabulary meant to be utilized by multiple complex variant structurally resonant AI modules.
A code base for Automated Relational Feature Engineering
PyTorch implementations of geometric learning algorithms and architectures. Subset of CAMOC.
Neural implicit reconstruction experiments for the Vector Neuron paper
Code for SIGGRAPH paper CNNs on Surfaces using Rotation-Equivariant Features
Topological Cognitive Diffusive Emergence (TCDE) - A Geometric Framework for Emergent Intelligence
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