Cover Image

Energy Considerations of Large Language Model Inference and Efficiency Optimizations

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Fernandez, Jared, Na, Clara, Tiwari, Vashisth, Bisk, Yonatan, Luccioni, Sasha, Strubell, Emma
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Energy and Carbon Considerations of Fine-Tuning BERT
by: Wang, Xiaorong, et al.
Published: (2023)

Gradient Localization Improves Lifelong Pretraining of Language Models
by: Fernandez, Jared, et al.
Published: (2024)

Language Models Need Inductive Biases to Count Inductively
by: Chang, Yingshan, et al.
Published: (2024)

Power Hungry Processing: Watts Driving the Cost of AI Deployment?
by: Luccioni, Alexandra Sasha, et al.
Published: (2023)

Hardware Scaling Trends and Diminishing Returns in Large-Scale Distributed Training
by: Fernandez, Jared, et al.
Published: (2024)

Scalable Data Ablation Approximations for Language Models through Modular Training and Merging
by: Na, Clara, et al.
Published: (2024)

Holistically Evaluating the Environmental Impact of Creating Language Models
by: Morrison, Jacob, et al.
Published: (2025)

From Efficiency Gains to Rebound Effects: The Problem of Jevons' Paradox in AI's Polarized Environmental Debate
by: Luccioni, Alexandra Sasha, et al.
Published: (2025)

Understanding Efficiency: Quantization, Batching, and Serving Strategies in LLM Energy Use
by: Delavande, Julien, et al.
Published: (2026)

Looking beyond the next token
by: Thankaraj, Abitha, et al.
Published: (2025)

Tools Fail: Detecting Silent Errors in Faulty Tools
by: Sun, Jimin, et al.
Published: (2024)

Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws
by: Sardana, Nikhil, et al.
Published: (2023)

AE-LLM: Adaptive Efficiency Optimization for Large Language Models
by: Tanaka, Kaito, et al.
Published: (2026)

SpreadsheetArena: Decomposing Preference in LLM Generation of Spreadsheet Workbooks
by: Kundurthy, Srivatsa, et al.
Published: (2026)

Enhancing Inference Efficiency of Large Language Models: Investigating Optimization Strategies and Architectural Innovations
by: Tyukin, Georgy
Published: (2024)

Towards Resource-Efficient LLMs: End-to-End Energy Accounting of Distillation Pipelines
by: Lambert, Katherine, et al.
Published: (2026)

Self-Regulation and Requesting Interventions
by: Min, So Yeon, et al.
Published: (2025)

Sequence-Level Leakage Risk of Training Data in Large Language Models
by: Tiwari, Trishita, et al.
Published: (2024)

Sparse Upcycling: Inference Inefficient Finetuning
by: Doubov, Sasha, et al.
Published: (2024)

Video Killed the Energy Budget: Characterizing the Latency and Power Regimes of Open Text-to-Video Models
by: Delavande, Julien, et al.
Published: (2025)

Kinetics: Rethinking Test-Time Scaling Laws
by: Sadhukhan, Ranajoy, et al.
Published: (2025)

Dynamic Subset Tuning: Expanding the Operational Range of Parameter-Efficient Training for Large Language Models
by: Stahlberg, Felix, et al.
Published: (2024)

Learning Model Successors
by: Chang, Yingshan, et al.
Published: (2025)

Strategic Polysemy in AI Discourse: A Philosophical Analysis of Language, Hype, and Power
by: LaCroix, Travis, et al.
Published: (2026)

Small Talk, Big Impact: The Energy Cost of Thanking AI
by: Delavande, Julien, et al.
Published: (2026)

Optimization Strategies for Enhancing Resource Efficiency in Transformers & Large Language Models
by: Wallace, Tom, et al.
Published: (2025)

CATS: Contextually-Aware Thresholding for Sparsity in Large Language Models
by: Lee, Donghyun, et al.
Published: (2024)

CORM: Cache Optimization with Recent Message for Large Language Model Inference
by: Dai, Jincheng, et al.
Published: (2024)

Optimizing Large Language Models with an Enhanced LoRA Fine-Tuning Algorithm for Efficiency and Robustness in NLP Tasks
by: Hu, Jiacheng, et al.
Published: (2024)

Under the Influence: Quantifying Persuasion and Vigilance in Large Language Models
by: Robinson, Sasha, et al.
Published: (2026)

Explore Theory of Mind: Program-guided adversarial data generation for theory of mind reasoning
by: Sclar, Melanie, et al.
Published: (2024)

Adversarial Evasion Attack Efficiency against Large Language Models
by: Vitorino, João, et al.
Published: (2024)

Inference-Cost-Aware Dynamic Tree Construction for Efficient Inference in Large Language Models
by: Hong, Yinrong, et al.
Published: (2025)

TreePO: Bridging the Gap of Policy Optimization and Efficacy and Inference Efficiency with Heuristic Tree-based Modeling
by: Li, Yizhi, et al.
Published: (2025)

Task-Specific Efficiency Analysis: When Small Language Models Outperform Large Language Models
by: Cao, Jinghan, et al.
Published: (2026)

FlashDecoding++: Faster Large Language Model Inference on GPUs
by: Hong, Ke, et al.
Published: (2023)

Experimental Design for Active Transductive Inference in Large Language Models
by: Mukherjee, Subhojyoti, et al.
Published: (2024)

Toward Sustainable GenAI using Generation Directives for Carbon-Friendly Large Language Model Inference
by: Li, Baolin, et al.
Published: (2024)

DebateBench: A Challenging Long Context Reasoning Benchmark For Large Language Models
by: Tiwari, Utkarsh, et al.
Published: (2025)

SOTOPIA: Interactive Evaluation for Social Intelligence in Language Agents
by: Zhou, Xuhui, et al.
Published: (2023)