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Computational Efficiency

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Methods and optimizations to reduce the computational resources (e.g., time, memory, or power) needed for training and inference in models. This involves techniques that streamline processing, optimize algorithms, or leverage hardware to enhance performance without compromising accuracy.

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/fgp-code/fgp

공식 코드

FGP: Feature-Gradient-Prune for Efficient Convolutional Layer Pruning

https://github.com/fighoture/moe_unsupervised_pruning

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Cluster-Driven Expert Pruning for Mixture-of-Experts Large Language Models

https://github.com/fireredteam/fireredasr

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FireRedASR: Open-Source Industrial-Grade Mandarin Speech Recognition Models from Encoder-Decoder to LLM Integration

https://github.com/fishmoon1234/nonlocal-attention-operator

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Neural Interpretable PDEs: Harmonizing Fourier Insights with Attention for Scalable and Interpretable Physics Discovery

https://github.com/flyfree5/lahore

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Large Language Model Can Be a Foundation for Hidden Rationale-Based Retrieval

https://github.com/focaslab/stl_stt

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Approximation-free Control for Signal Temporal Logic Specifications using Spatiotemporal Tubes

https://github.com/forgee-master/HADL

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HADL Framework for Noise Resilient Long-Term Time Series Forecasting

https://github.com/foundationvision/flashvideo

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FlashVideo:Flowing Fidelity to Detail for Efficient High-Resolution Video Generation

https://github.com/fra0013to/ginn

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Sparse Implementation of Versatile Graph-Informed Layers

https://github.com/frankxwang/dpo-prefix-sharing

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Accelerating Direct Preference Optimization with Prefix Sharing

https://github.com/fschmid56/efficientat

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Efficient Large-scale Audio Tagging via Transformer-to-CNN Knowledge Distillation

https://github.com/fsoft-aic/lassobo

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High Dimensional Bayesian Optimization using Lasso Variable Selection

https://github.com/fudan-zvg/ego3rt

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Learning Ego 3D Representation as Ray Tracing

https://github.com/fudan-zvg/realengine

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RealEngine: Simulating Autonomous Driving in Realistic Context

https://github.com/fudan-zvg/soft

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Softmax-free Linear Transformers

https://github.com/futurecomputing4ai/hadamard-derived-linear-binding

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A Walsh Hadamard Derived Linear Vector Symbolic Architecture

https://github.com/fyyfu/headkv

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Not All Heads Matter: A Head-Level KV Cache Compression Method with Integrated Retrieval and Reasoning

https://github.com/gaa-uam/c-gb

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Condensed Gradient Boosting

https://github.com/gair-nlp/limopro

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LIMOPro: Reasoning Refinement for Efficient and Effective Test-time Scaling

https://github.com/gamepiaynmo/lrmi

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Robust and Fast Measure of Information via Low-rank Representation

https://github.com/ganeshbabu1604/ccpgmm

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A consensus-constrained parsimonious Gaussian mixture model for clustering hyperspectral images

https://github.com/ganguli-lab/pathint

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Continual Learning Through Synaptic Intelligence

https://github.com/gdam90/hyp2nav

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Hyp2Nav: Hyperbolic Planning and Curiosity for Crowd Navigation

https://github.com/gdy-scu/FlightBERT_PP_V2

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A Non-autoregressive Multi-Horizon Flight Trajectory Prediction Framework with Gray Code Representation

https://github.com/geethen/geeconformal

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Uncertainty quantification for probabilistic machine learning in earth observation using conformal prediction

https://github.com/gemelo-ai/vocos

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Vocos: Closing the gap between time-domain and Fourier-based neural vocoders for high-quality audio synthesis

https://github.com/gemyxzhang/neural-subhalo-slope

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Inferring subhalo effective density slopes from strong lensing observations with neural likelihood-ratio estimation

https://github.com/genxproject/genx

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Effects of charging and discharging capabilities on trade-offs between model accuracy and computational efficiency in pumped thermal electricity storage

https://github.com/gerdm/weighted-likelihood-filter

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Outlier-robust Kalman Filtering through Generalised Bayes

https://github.com/giakoumoglou/distillers

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Relational Representation Distillation

https://github.com/gimpong/CVPR25-Condenser

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Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning

https://github.com/giodiro/nystromkoopman

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Estimating Koopman operators with sketching to provably learn large scale dynamical systems

https://github.com/giubots/vision-enabled-dialogue

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I Was Blind but Now I See: Implementing Vision-Enabled Dialogue in Social Robots

https://github.com/gjgjh/ptz-calib

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PTZ-Calib: Robust Pan-Tilt-Zoom Camera Calibration

https://github.com/gmc-drl/awesome-metabbo

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Toward Automated Algorithm Design: A Survey and Practical Guide to Meta-Black-Box-Optimization

https://github.com/gmum/PALATE

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PALATE: Peculiar Application of the Law of Total Expectation to Enhance the Evaluation of Deep Generative Models

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.