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UUtah CS 6966 Interpretability of LLMs Spring 2026 Course wrap

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UUtah CS 6966 Interpretability of LLMs Spring 2026 Influence functions

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UUtah CS 6966 Interpretability of LLMs Spring 2026 Chain-of-thought (CoT) unfaithfulness

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UUtah CS 6966 Interpretability of LLMs Spring 2026 Review of language model reasoning

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UUtah CS 6966 Interpretability of LLMs Spring 2026 Steering Part 2

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UUtah CS 6966 Interpretability of LLMs Spring 2026 Steering Part 1

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UUtah CS 6966 Interpretability of LLMs Spring 2026 Induction heads & Function vectors

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UUtah CS 6966 Interpretability of LLMs Spring 2026 QK & OV circuits

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UUtah CS 6966 Interpretability of LLMs Spring 2026 Arithmetic circuits & Course review

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UUtah CS 6966 Interpretability of LLMs Spring 2026 Attribution patching

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UUtah CS 6966 Interpretability of LLMs Spring 2026 Activation patching

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UUtah CS 6966 Interpretability of LLMs Spring 2026 Direct logit attribution & Logit lens

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UUtah CS 6966 Interpretability of LLMs Spring 2026 Model diffing with crosscoders

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UUtah CS 6966 Interpretability of LLMs Spring 2026 Probing Part 2

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UUtah CS 6966 Interpretability of LLMs Spring 2026 Course review & Probing

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UUtah CS 6966 Interpretability of LLMs Spring 2026 Attribution graphs Edge weights & pruning

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UUtah CS 6966 Interpretability of LLMs Spring 2026 CLT → Attribution graph

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UUtah CS 6966 Interpretability of LLMs Spring 2026 Transcoders

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UUtah CS 6966 Interpretability of LLMs Spring 2026 SAE advances Part 2

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UUtah CS 6966 Interpretability of LLMs Spring 2026 SAE use cases & training advances

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UUtah CS 6966 Interpretability of LLMs Spring 2026 Evaluating SAE feature descriptions

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UUtah CS 6966 Interpretability of LLMs Spring 2026 Generating SAE feature descriptions

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UUtah CS 6966 Interpretability of LLMs Spring 2026 Linear representation hypothesis

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UUtah CS 6966 Interpretability of LLMs Spring 2026 Sparse autoencoders Basics

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UUtah CS 6966 Interpretability of LLMs Spring 2026 Superposition

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(Q)LoRA; Course wrap

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Quantization & KV cache

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DPO & Reasoning LMs

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SFT data & RLHF

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LLM-as-judge; Instruction finetuning SFT

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