12 papers
Kilobyte Models: Neural Networks as a Seed and a Quantized Latent
Sahil Rajesh Dhayalkar
The cost of storing and transmitting a trained neural network scales with its parameter count, a bottleneck for over-the-air updates, on-device libraries, and other bandwidth-bound…
Overcoming the Impedance Mismatch: A Theoretical Roadmap for Fusing Foundation Models and Knowledge Graphs
Sahil Rajesh Dhayalkar
Modern artificial intelligence remains fundamentally divided between the continuous, probabilistic spaces of Foundation Models and the discrete, deterministic structures of Knowled…
Logic-Gated Time-Shared Feedforward Networks for Alternating Finite Automata: Exact Simulation and Learnability
Sahil Rajesh Dhayalkar
We present a formal and constructive framework for simulating Alternating Finite Automata (AFAs) using Logic-Gated Time-Shared Feedforward Networks (LG-TS-FFNs). Unlike prior neura…
Reasoning Stabilization Point: A Training-Time Signal for Stable Evidence and Shortcut Reliance
Sahil Rajesh Dhayalkar
Fine-tuning pretrained language models can improve task performance while subtly altering the evidence a model relies on. We propose a training-time interpretability view that trac…
Attention as Binding: A Vector-Symbolic Perspective on Transformer Reasoning
Sahil Rajesh Dhayalkar
Transformer-based language models display impressive reasoning-like behavior, yet remain brittle on tasks that require stable symbolic manipulation. This paper develops a unified p…
Particle Filter Made Simple: A Step-by-Step Beginner-friendly Guide
Sahil Rajesh Dhayalkar
The particle filter is a powerful framework for estimating hidden states in dynamic systems where uncertainty, noise, and nonlinearity dominate. This mini-book offers a clear and s…