Hyperspherical Semantic Trajectory Analysis: Mapping Technological Diffusion across Academic Preprints, Patent Signals, and Compute Scaling

arXiv:2609.35845 · cs.CL, cs.LG · Submitted 2026-09-25 · Read on arXiv

cs.CL, cs.LG

Submitted: 2026-09-25

Updated: 2026-09-25

Terminology

• Embeddings — 8× in this paper · explained in 2 episodes
• Transformer — 7× in this paper · explained in 2 episodes
• Clustering — 6× in this paper · explained in 2 episodes
• Alignment — 4× in this paper · explained in 1 episode
• Davies-Bouldin Index — 3× in this paper
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Hyperspherical Semantic Trajectory Analysis — 3× in this paper
• Benchmark — 2× in this paper · explained in 2 episodes
• Latent Space — 2× in this paper · explained in 7 episodes
• Semantic Drift — 2× in this paper · explained in 3 episodes
• Alignment Techniques — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• In-Context Learning — 1× in this paper · explained in 4 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• Prompt Engineering — 1× in this paper · explained in 4 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Scaling Laws — 1× in this paper · explained in 4 episodes
• Steering — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes
• Uniform Manifold Approximation and Projection — 1× in this paper

Sources

• UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
• Scaling Laws for Neural Language Models
• Training Compute-Optimal Large Language Models
• GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models

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