3 papers
cs.AI2026
A Persistent State for Auditable Mixture-of-Experts Routing
Abdurrahman Javat, Allan Kazakov
Mixture-of-Experts (MoE) models repeatedly route tokens to sparse subsets of experts, but conventional routers expose no routing-specific record of how cross-layer influences accum…
cs.AI2026
Accepted Prefixes Are Not All You Need: A Negative Result on PEFT-Based Block-Diffusion Drafting
Abdurrahman Javat, Allan Kazakov
Speculative decoding accelerates autoregressive language model inference by using a cheap drafter to propose multiple future tokens and a target model to verify them. A common desi…
cs.PF2026
Silicon Showdown: Performance, Efficiency, and Ecosystem Barriers in Consumer-Grade LLM Inference
Abdurrahman Javat, Allan Kazakov
The operational landscape of local Large Language Model (LLM) inference has shifted from lightweight models to datacenter-class weights exceeding 70B parameters, creating profound…