Fix tex formatting: lists for related work, limitations, comparisons

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
2026-04-06 19:52:15 +07:00
parent 2a4e0c9713
commit 3fedc87f0c
4 changed files with 79 additions and 51 deletions

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@@ -3,14 +3,14 @@
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@@ -36,9 +37,11 @@
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@@ -48,9 +48,13 @@ the model is exactly as it was---no trace, no residue.
The closer analogy is post-hypnotic suggestion: a trigger installed externally,
fired without the subject's awareness, removable without leaving a mark.
Fine-tuning modifies weights. RAG re-encodes text each time. LoRA requires
gradients. In-context learning vanishes with the conversation. CRI persists
across sessions without touching the model.
\begin{itemize}
\item Fine-tuning modifies weights and causes catastrophic forgetting.
\item RAG re-encodes text each time --- no persistent behavioral change.
\item LoRA requires gradients.
\item In-context learning vanishes with the conversation.
\item CRI persists across sessions without touching the model.
\end{itemize}
%───────────────────────────────────────────────
\section{Method}
@@ -130,7 +134,7 @@ diverges:
\begin{table}[h]
\centering
\begin{tabular}{llll}
\begin{tabular}{lll}
\toprule
Backbone & Post-bias behavior & Fluent? \\
\midrule
@@ -212,27 +216,44 @@ operating in the model's internal space.
%───────────────────────────────────────────────
\section{Related Work}
\textbf{Pavlov}~(1927) described hypnotic suggestion as the best example of a
conditioned reflex in humans. \textbf{``Hypnosis and the Conditioned Reflex''}
(1930) formalized this: suggestion installs stimulus-response links that fire
without the subject's awareness. CRI implements the same mechanism on
transformers: activation pattern (CS) paired with logit biases (US) produces
token sequence (CR). \textbf{Raz et~al.}~(2005) showed post-hypnotic suggestion
reduces conflict in human brains by modulating activity in specific
regions---external behavioral modification without awareness, analogous to
CRI's logit injection. \textbf{Skinner}~(1938): operant conditioning. CRI
currently performs respondent conditioning only; bias modulation via reward is a
natural extension.
\subsection{Behavioral Conditioning}
\textbf{CAMELoT} \citep{jang2024camelot}: KV pairs from attention, injected as
prefixes. \textbf{EM-LLM} \citep{fountas2024emllm}: KV cache extension.
\textbf{Larimar} \citep{das2024larimar}: memory matrix, requires training.
All inject at attention level. CRI injects at output logits---simpler, cheaper,
no attention recomputation.
\begin{itemize}
\item \textbf{Pavlov}~(1927) described hypnotic suggestion as the best example
of a conditioned reflex in humans.
\item \textbf{``Hypnosis and the Conditioned Reflex''}~(1930) formalized this:
suggestion installs stimulus-response links that fire without awareness.
\item \textbf{Raz et~al.}~(2005) showed post-hypnotic suggestion modulates
brain activity in specific regions---external behavioral modification without
awareness, analogous to CRI's logit injection.
\item \textbf{Skinner}~(1938): operant conditioning. CRI currently performs
respondent conditioning only; bias modulation via reward is a natural
extension.
\end{itemize}
\textbf{RAG} \citep{lewis2020rag}: retrieves text, re-encodes. RAG informs; CRI
conditions. \textbf{ROME/MEMIT} \citep{meng2022rome,meng2023memit}: rank-one
weight edits. CRI modifies zero weights.
CRI implements the Pavlovian mechanism on transformers: activation pattern (CS)
paired with logit biases (US) produces token sequence (CR).
\subsection{Training-Free External Memory}
\begin{itemize}
\item \textbf{CAMELoT} \citep{jang2024camelot}: KV pairs from attention,
injected as prefixes.
\item \textbf{EM-LLM} \citep{fountas2024emllm}: KV cache extension.
\item \textbf{Larimar} \citep{das2024larimar}: memory matrix, requires training.
\end{itemize}
All inject at the attention level. CRI injects at output logits---simpler,
cheaper, no attention recomputation.
\subsection{Other Approaches}
\begin{itemize}
\item \textbf{RAG} \citep{lewis2020rag}: retrieves text, re-encodes into
context. RAG informs; CRI conditions.
\item \textbf{ROME/MEMIT} \citep{meng2022rome,meng2023memit}: rank-one weight
edits. CRI modifies zero weights.
\end{itemize}
%───────────────────────────────────────────────
\section{Limitations}