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cs.LG2026
Training and Inference Dynamics of PLDR-LLMs: Row-Map Collapse, Renormalization, and Predictive Reduction
Burc Gokden
This monograph develops a unified account of training and inference in Power Law Decoder Representation language models (PLDR-LLMs). Exact finite work identities decompose changes…
cs.LG2026
Power law graph attention: exact generalization of scaled dot-product attention, empirical collapse at inference
Burc Gokden
The Large Language Model from Power Law Decoder Representations (PLDR-LLM) and its attention, Power Law Graph Attention (PLGA), replace the fixed bilinear form of scaled dot-produc…
cs.AI2026
PLDR-LLMs Reason At Self-Organized Criticality
Burc Gokden
We show that PLDR-LLMs pretrained at self-organized criticality exhibit reasoning at inference time. The characteristics of PLDR-LLM deductive outputs at criticality is similar to…