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Knowledge Distillation

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하위 태스크: 2
평가표: 11
보존된 평가 기록: 90

Knowledge distillation is the process of transferring knowledge from a large model to a smaller one. While large models (such as very deep neural networks or ensembles of many models) have higher knowledge capacity than small models, this capacity might not be fully utilized.

코드

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

https://github.com/CASTLE-Benchmark/CASTLE-Benchmark

공식 코드

CASTLE: Benchmarking Dataset for Static Code Analyzers and LLMs towards CWE Detection

https://github.com/CBCodeHub/Mining-Gym

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Mining-Gym: A Configurable RL Benchmarking Environment for Truck Dispatch Scheduling

https://github.com/CHNPAT005/PCEPTG-MM-NUFFT

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Malliavin-Mancino estimators implemented with non-uniform fast Fourier transforms

https://github.com/COSPOV/ProWRAS

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A multi-schematic classifier-independent oversampling approach for imbalanced datasets

https://github.com/CVLAB-Unibo/omeganet

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Distilled Semantics for Comprehensive Scene Understanding from Videos

https://github.com/CXH-Research/IRFormer

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Implicit Multi-Spectral Transformer: An Lightweight and Effective Visible to Infrared Image Translation Model

https://github.com/CancerDataScience/NuCLS

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NuCLS: A scalable crowdsourcing, deep learning approach and dataset for nucleus classification, localization and segmentation

https://github.com/CapsuleEndoscope/EndoSLAM

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EndoSLAM Dataset and An Unsupervised Monocular Visual Odometry and Depth Estimation Approach for Endoscopic Videos: Endo-SfMLearner

https://github.com/Cc-Hy/CMKD

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Cross-Modality Knowledge Distillation Network for Monocular 3D Object Detection

https://github.com/Chan-Sun/DKAN

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A New Knowledge Distillation Network for Incremental Few-Shot Surface Defect Detection

https://github.com/ChanYunHin/FedHe

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FedHe: Heterogeneous Models and Communication-Efficient Federated Learning

https://github.com/ChangWeiTan/TSRegression

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Monash University, UEA, UCR Time Series Extrinsic Regression Archive

https://github.com/China-UK-ZSL/Resources_for_KZSL

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Benchmarking Knowledge-driven Zero-shot Learning

https://github.com/ChristopherSweeney/SlimNets

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SlimNets: An Exploration of Deep Model Compression and Acceleration

https://github.com/Chutlhu/dEchorate

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dEchorate: a Calibrated Room Impulse Response Database for Echo-aware Signal Processing

https://github.com/Cloud-CV/EvalAI

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EvalAI: Towards Better Evaluation Systems for AI Agents

https://github.com/CoderMusou/MECT4CNER

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MECT: Multi-Metadata Embedding based Cross-Transformer for Chinese Named Entity Recognition

https://github.com/CompNet/WikiSynch

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WAC: A Corpus of Wikipedia Conversations for Online Abuse Detection

https://github.com/ControlNet/LAV-DF

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Do You Really Mean That? Content Driven Audio-Visual Deepfake Dataset and Multimodal Method for Temporal Forgery Localization

https://github.com/CriticBench/CriticBench

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CriticBench: Benchmarking LLMs for Critique-Correct Reasoning

https://github.com/Cyno2232/UBENCH

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UBENCH: Benchmarking Uncertainty in Large Language Models with Multiple Choice Questions

https://github.com/D-X-Y/AutoDL-Projects

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NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size

https://github.com/D-X-Y/NAS-Projects

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Network Pruning via Transformable Architecture Search

https://github.com/DEAkimov/learn_to_move

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Distributed Soft Actor-Critic with Multivariate Reward Representation and Knowledge Distillation

https://github.com/DISL-Lab/FineSurE

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FineSurE: Fine-grained Summarization Evaluation using LLMs

https://github.com/DLweighting/Distribution-Learning-based-weighting

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Weighting-Based Treatment Effect Estimation via Distribution Learning

https://github.com/DPBayes/Towards-Efficient-Scalable-Training-DP-DL

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Towards Efficient and Scalable Training of Differentially Private Deep Learning

https://github.com/DTennant/distill_visual_priors

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Distilling Visual Priors from Self-Supervised Learning

https://github.com/DamianoBrunori/MultiUAV-OpenAIGym

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A Reinforcement Learning Environment for Multi-Service UAV-enabled Wireless Systems

https://github.com/DandyQi/CentraBert

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A Flexible Multi-Task Model for BERT Serving

https://github.com/Daniel-Gong/ChatGPT_WM

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Working Memory Capacity of ChatGPT: An Empirical Study

https://github.com/Daniel-xsy/RoboBEV

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Benchmarking and Improving Bird's Eye View Perception Robustness in Autonomous Driving

https://github.com/DanielSHKao/StableKD

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StableKD: Breaking Inter-block Optimization Entanglement for Stable Knowledge Distillation

https://github.com/DataScienceUIBK/Rankify

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Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation

https://github.com/DebeshJha/ColonSegNet

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Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning

https://github.com/DebeshJha/Kvasir-Instrument

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Kvasir-Instrument: Diagnostic and therapeutic tool segmentation dataset in gastrointestinal endoscopy

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