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Papers matching “inference efficiency” 8

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Energy Efficiency of Locally Deployed LLMs: A Preliminary Quantitative GPU Power Benchmark on Consumer Hardware
2026 arXiv (Cornell University) preprint Engineering Green IT and Sustainability Open access

Philipp M. Zähl, Elja Dalipaj, Anika Hennig, Timon Bayer

0

citations
Optimizing Binary and Ternary Neural Network Inference on RRAM Crossbars using CIM-Explorer
2025 arXiv (Cornell University) preprint Engineering Advanced Memory and Neural Computing Open access

Rebecca Pelke, José Cubero-Cascante, Nils Bosbach, Niklas Degener, Florian Idrizi, Lennart M. Reimann, +2 more

1

citations
MambaCSP: Hybrid-Attention State Space Models for Hardware-Efficient Channel State Prediction
2026 arXiv (Cornell University) preprint Engineering Advanced Wireless Communication Techniques Open access

Aladin Djuhera, Haris Gacanin, Holger Boche

2

citations
CoMoCAVs: Cohesive Decision-Guided Motion Planning for Connected and Autonomous Vehicles with Multi-Policy Reinforcement Learning
2025 arXiv (Cornell University) preprint Engineering Autonomous Vehicle Technology and Safety Open access

Pan Hu

1

citations
Structure-Enhanced Features and Quality-Aware Dynamic Anchor Scoring for Robust Lane Detection
2026 arXiv (Cornell University) preprint Engineering Autonomous Vehicle Technology and Safety Open access

Weize Cai, Yongqi Dong, Zhida Shao, Yichen Liu, Zixin Fu

0

citations
Online Transformers with Spiking Neurons for Fast Prosthetic Hand Control
2023 arXiv (Cornell University) preprint Engineering Muscle activation and electromyography studies Open access

Nathan Leroux, Jan Finkbeiner, Emre Neftci

0

citations
A Fast and Energy-Efficient Latch-Based Memristive Analog Content-Addressable Memory
2026 arXiv (Cornell University) preprint Engineering Advanced Memory and Neural Computing Open access

Paul-Philipp Manea, Aishwarya Natarajan, Jim Ignowski, John Paul Strachan, Luca Buonanno

1

citations
Perspective: Content-addressable memories as a computing primitive for today's AI and beyond
2026 arXiv (Cornell University) preprint Engineering Advanced Memory and Neural Computing Open access

Paul-Philipp Manea, Bo Wen, Peiyi He, Can Li, John Paul Strachan

0

citations

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