Cut the cost of agentic LLM memory by deciding what to write before calling an LLM. SAGE is a closed-form novelty gate that routes new facts to ADD, redundant ones to SKIP, and only sends genuinely ambiguous cases to an LLM — 3.4× cheaper, 2.5× faster writes.
A novel teacher‑free distillation method that replaces live teacher inference with compact precomputed random projection teacher fingerprints, enabling storage-efficient, high-performance knowledge transfer and enhanced student training.
Official Repo of OpenArchX Framework.
A hands-on lab comparing PTQ INT8, magnitude pruning, and knowledge distillation on small CNNs.
Layer-adaptive quantization of diffusion models using Fisher Information (LAQFI), presented at IEIE 2024.
O(N) Linear Complexity Transformer - 125x faster than standard attention using cumulative sum trick. Pure PyTorch implementation.
First 1-bit (BitNet b1.58) recursive reasoner for Sudoku-Extreme - distilled from a 7M-param FP TRM teacher into a 1.4 MB ternary student
Notes and Labs from MIT 6.5940, (Fall 2023) lecture.
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