Understanding Confabulation and Rethinking Reconstruction in Activation Explanations

arXiv:2609.33702 · cs.CL, cs.AI · Submitted 2026-09-27 · Read on arXiv

cs.CL, cs.AI

Submitted: 2026-09-27

Updated: 2026-09-27

Terminology

• Accuracy — 16× in this paper · explained in 1 episode
• Diffusion Model — 4× in this paper · explained in 8 episodes
• Adam — 3× in this paper · explained in 2 episodes
• Aggregation — 3× in this paper · explained in 1 episode
• Diffusion Models — 2× in this paper · explained in 6 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Distribution Shift — 1× in this paper · explained in 5 episodes
• F1 Score — 1× in this paper · explained in 3 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Flow Matching — 1× in this paper · explained in 8 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Information Gain — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• KV cache — 1× in this paper · explained in 3 episodes
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Reward Function — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes

Sources

• DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression
• Train the Model, Not the Reader: Decodability Supervision for Verifiable Activation Explanations
• Mutual Information and Minimum Mean-square Error in Gaussian Channels
• Denoising Diffusion Probabilistic Models
• Activation Oracles: Training and Evaluating LLMs as General-Purpose Activation Explainers
• Understanding Diffusion Objectives as the ELBO with Simple Data Augmentation
• Variational Diffusion Models
• Continuous control with deep reinforcement learning
• LatentQA: Teaching LLMs to Decode Activations Into Natural Language
• Qwen2.5 Technical Report

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