PULSE: Identifying Demonstration-Utility Features with Sparse Autoencoders

arXiv:2609.32469 · cs.AI, cs.CL, cs.LG · Submitted 2026-09-26 · Read on arXiv

cs.AI, cs.CL, cs.LG

Submitted: 2026-09-26

Updated: 2026-09-26

Terminology

• Accuracy — 34× in this paper · explained in 1 episode
• In-Context Learning — 18× in this paper · explained in 4 episodes
• Cosine Similarity — 9× in this paper · explained in 3 episodes
• Benchmark — 7× in this paper · explained in 2 episodes
• Redundancy — 7× in this paper · explained in 2 episodes
• Alignment — 4× in this paper · explained in 1 episode
• Embeddings — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Commentary — 3× in this paper · explained in 2 episodes
• Consistency — 3× in this paper · explained in 3 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Sparse Autoencoders (SAEs) — 2× in this paper · explained in 3 episodes
• Transferability — 2× in this paper · explained in 4 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• In-Context Learning (ICL) — 1× in this paper · explained in 5 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Reasoning Traces — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Tokenization — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Verifier — 1× in this paper · explained in 2 episodes

Sources

• MVI-Bench: A Comprehensive Benchmark for Evaluating Robustness to Misleading Visual Inputs in LVLMs
• Training Verifiers to Solve Math Word Problems
• Toy Models of Superposition
• The Llama 3 Herd of Models
• Llama Scope: Extracting Millions of Features from Llama-3.1-8B with Sparse Autoencoders
• Dr.ICL: Demonstration-Retrieved In-context Learning
• In-context Learning and Induction Heads
• Jumping Ahead: Improving Reconstruction Fidelity with JumpReLU Sparse Autoencoders
• Gemma 2: Improving Open Language Models at a Practical Size

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