High Efficiency
High efficiency in various computational domains is a central research theme, aiming to minimize resource consumption (time, memory, energy) while maintaining or improving performance. Current efforts focus on developing novel algorithms and architectures, such as optimized Thompson sampling for reinforcement learning, sparse attention mechanisms for transformers, and efficient model compression techniques, to achieve this goal across diverse applications including natural language processing, computer vision, and robotics. These advancements are crucial for deploying complex AI models on resource-constrained devices and for accelerating scientific discovery in data-intensive fields.
Papers
MetaPix: A Data-Centric AI Development Platform for Efficient Management and Utilization of Unstructured Computer Vision Data
Sai Vishwanath Venkatesh, Atra Akandeh, Madhu Lokanath
An Efficient Projection-Based Next-best-view Planning Framework for Reconstruction of Unknown Objects
Zhizhou Jia, Shaohui Zhang, Qun Hao
Symmetry-Based Structured Matrices for Efficient Approximately Equivariant Networks
Ashwin Samudre, Mircea Petrache, Brian D. Nord, Shubhendu Trivedi
OATH: Efficient and Flexible Zero-Knowledge Proofs of End-to-End ML Fairness
Olive Franzese, Ali Shahin Shamsabadi, Hamed Haddadi
Improving the Efficiency of Visually Augmented Language Models
Paula Ontalvilla, Aitor Ormazabal, Gorka Azkune
Efficient and Personalized Mobile Health Event Prediction via Small Language Models
Xin Wang, Ting Dang, Vassilis Kostakos, Hong Jia
Collaborating for Success: Optimizing System Efficiency and Resilience Under Agile Industrial Settings
Sunny Katyara, Suchita Sharma, Praveen Damacharla, Carlos Garcia Santiago, Francis O'Farrell, Philip Long
Efficient and Reliable Vector Similarity Search Using Asymmetric Encoding with NAND-Flash for Many-Class Few-Shot Learning
Hao-Wei Chiang, Chi-Tse Huang, Hsiang-Yun Cheng, Po-Hao Tseng, Ming-Hsiu Lee, An-Yeu (Andy)Wu
Efficient Privacy-Preserving KAN Inference Using Homomorphic Encryption
Zhizheng Lai, Yufei Zhou, Peijia Zheng, Lin Chen
Efficient One-Step Diffusion Refinement for Snapshot Compressive Imaging
Yunzhen Wang, Haijin Zeng, Shaoguang Huang, Hongyu Chen, Hongyan Zhang
Learning to Compress Contexts for Efficient Knowledge-based Visual Question Answering
Weixi Weng, Jieming Zhu, Hao Zhang, Xiaojun Meng, Rui Zhang, Chun Yuan
Efficient and Unbiased Sampling of Boltzmann Distributions via Consistency Models
Fengzhe Zhang, Jiajun He, Laurence I. Midgley, Javier Antorán, José Miguel Hernández-Lobato
OneGen: Efficient One-Pass Unified Generation and Retrieval for LLMs
Jintian Zhang, Cheng Peng, Mengshu Sun, Xiang Chen, Lei Liang, Zhiqiang Zhang, Jun Zhou, Huajun Chen, Ningyu Zhang
Efficient learning-based sound propagation for virtual and real-world audio processing applications
Anton Jeran Ratnarajah
AnyMatch -- Efficient Zero-Shot Entity Matching with a Small Language Model
Zeyu Zhang, Paul Groth, Iacer Calixto, Sebastian Schelter
A First Look At Efficient And Secure On-Device LLM Inference Against KV Leakage
Huan Yang, Deyu Zhang, Yudong Zhao, Yuanchun Li, Yunxin Liu
On The Role of Prompt Construction In Enhancing Efficacy and Efficiency of LLM-Based Tabular Data Generation
Banooqa Banday, Kowshik Thopalli, Tanzima Z. Islam, Jayaraman J. Thiagarajan