8 citations · 17 across the 11 of their papers we have counts for
14 papers
Energy Consumption Analysis of Discrete Diffusion and Autoregressive Language Models
Boris Ruf, Marcin Detyniecki
As Large Language Models (LLMs) continue to scale, their energy consumption during inference has become a critical concern. While Autoregressive (AR) models are the industry standa…
The Cost of Context: Profiling the Energy Footprint of Input Tokens in Large Language Models
Boris Ruf, Marcin Detyniecki
The rapid adoption of Retrieval-Augmented Generation (RAG) and long-context LLMs has shifted the computational burden toward the prefill phase---the initial stage where the model p…
Energy Scaling Laws for Diffusion Models: Quantifying Compute in Image Generation
Aniketh Iyengar, Jiaqi Han, Boris Ruf +3
The rapidly growing computational demands of diffusion models for image generation have raised significant concerns about energy consumption and environmental impact. While existin…
Mitigating the Carbon Footprint of Chatbots as Consumers
Boris Ruf, Marcin Detyniecki
In the context of the high energy demand of large language models (LLMs) and growing concerns about global warming, there is significant demand for actionable recommendations that…
The "Huh?" Button: Improving Understanding in Educational Videos with Large Language Models
Boris Ruf, Marcin Detyniecki
We propose a simple way to use large language models (LLMs) in education. Specifically, our method aims to improve individual comprehension by adding a novel feature to online vide…
Open and Linked Data Model for Carbon Footprint Scenarios
Boris Ruf, Marcin Detyniecki
Carbon footprint quantification is key to well-informed decision making over carbon reduction potential, both for individuals and for companies. Many carbon footprint case studies…