1 citations · 1 across the 15 of their papers we have counts for
17 papers
SVR-MAD: A Bayesian-Inspired Framework for Posterior-Guided Multi-Agent Debate
Weifan Jiang, Rana Shahout, Minghao Li +4
Multi-Agent Debate (MAD) improves LLM-agent accuracy but suffers from rapid context growth, limiting scalability in larger multi-agent settings. Existing methods prune low-utility…
PALS: Power-Aware LLM Serving for Mixture-of-Experts Models
Can Hankendi, Rana Shahout, Minlan Yu +1
Large language model (LLM) inference has become a dominant workload in modern data centers, driving significant GPU utilization and energy consumption. While prior systems optimize…
Orla: A Library for Serving LLM-Based Multi-Agent Systems
Rana Shahout, Hayder Tirmazi, Minlan Yu +1
We introduce Orla, a library for constructing and running LLM-based agentic systems. Modern agentic applications consist of workflows that combine multiple LLM inference steps, too…
Predictive Scheduling for Efficient Inference-Time Reasoning in Large Language Models
Katrina Brown, Aneesh Muppidi, Rana Shahout
Large language models (LLMs) achieve state-of-the-art accuracy on complex reasoning tasks by generating multiple chain-of-thought (CoT) traces, but using a fixed token budget per q…
Distributed Recoverable Sketches (Extended Version)
Diana Cohen, Roy Friedman, Rana Shahout
Sketches are commonly used in computer systems and network monitoring tools to provide efficient query executions while maintaining a compact data representation. Switches and rout…
From Score Distributions to Balance: Plug-and-Play Mixture-of-Experts Routing
Rana Shahout, Colin Cai, Yilun Du +2
Mixture-of-Experts (MoE) models can scale parameter capacity by routing each token to a subset of experts through a learned gate function. While conditional routing reduces trainin…