5 papers · 1 filter
Network Topology Does Not Matter: The Breakdown of Classical Consensus in LLM Populations
Sahil Rajesh Dhayalkar
As multi-agent language model networks become widely deployed, predicting their collective behavior is a critical challenge. Classical distributed consensus theory relies on networ…
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…