Fisher-IRG: Fisher-Induced Local Invariant Representation Geometry across Language and Vision Models

arXiv:2609.36458 · cs.LG, cs.CL, cs.CV · Submitted 2026-09-29 · Read on arXiv

cs.LG, cs.CL, cs.CV

Submitted: 2026-09-29

Updated: 2026-09-29

Terminology

• Transformer — 11× in this paper · explained in 2 episodes
• Accuracy — 9× in this paper · explained in 1 episode
• Fisher Information — 7× in this paper · explained in 3 episodes
• Steering — 5× in this paper · explained in 2 episodes
• Activation Steering — 3× in this paper · explained in 4 episodes
• Cosine Similarity — 3× in this paper · explained in 3 episodes
• Frozen model — 3× in this paper · explained in 3 episodes
• Generative Model — 3× in this paper · explained in 2 episodes
• Generative Models — 3× in this paper · explained in 2 episodes
• Representation Learning — 3× in this paper · explained in 2 episodes
• Alignment — 2× in this paper · explained in 1 episode
• Consistency — 2× in this paper · explained in 3 episodes
• Contrastive Learning — 2× in this paper · explained in 5 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Latent Space — 2× in this paper · explained in 7 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Regularization — 1× in this paper · explained in 3 episodes

Sources

• Invariant Features in Language Models: Geometric Characterization and Model Attribution
• FishBack: Pullback Fisher Geometry for Optimal Activation Steering in Transformers

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