GitHub - Dicklesworthstone/llm_introspective_compression_and_metacognition: A novel approach for transformer model introspection that enables saving, compressing, and manipulating internal thought states for advanced capabilities like reasoning backtracking, latent thought optimization, and metacognitive control.
Real-Time Introspective Compression for Transformers
By Jeffrey Emanuel (and various collaborators of the electronic persuasion)
Written on April 1st, 2025
Introduction: Two Intertwined Problems
Transformer-based large language models (LLMs) face two significant limitations that restrict their capabilities:
Lack of Introspection: Unless specifically instrumented, transformer-based LLMs have no ability to explicitly access their own internal states—the activations in their feed-forward layers, at...
Read more at github.com