https://github.com/BM-K/KoSentenceBERT_SKT
Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation
Papers with Code 아카이브
Knowledge Distillation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 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/BM-K/KoSentenceBERT_SKTBERT
Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation
https://github.com/Bam4d/GVGAI_GYM
https://github.com/BecauseOfGAN/capston
https://github.com/BecauseOfGAN/capstone
https://github.com/BigBinnie/Benchmarking-LLM-based-Machine-Translation-on-Cultural-Awareness
https://github.com/Boese0601/DUT_AI_2020_mmdetection
https://github.com/BrightBlueCheese/Modeling-of-Time-varying-Wireless-Communication-Channel-with-Fading-and-Shadowing
https://github.com/Burf/tfdetection
https://github.com/ByteSumoLtd/pyESN
Echo State Networks with Self-Normalizing Activations on the Hyper-Sphere
https://github.com/CAMMA-public/cholect50
Data Splits and Metrics for Method Benchmarking on Surgical Action Triplet Datasets
https://github.com/CHNPAT005/PCEPTG-MSC
Malliavin-Mancino estimators implemented with non-uniform fast Fourier transforms
https://github.com/CXH-Research/UIE-UnFold
https://github.com/Caesarzhang/bert-zh
Well-Read Students Learn Better: On the Importance of Pre-training Compact Models
https://github.com/CahideSara/deneme
https://github.com/CanPeng123/Faster-ILOD
Faster ILOD: Incremental Learning for Object Detectors based on Faster RCNN
https://github.com/Capsar/DL-GenISP
https://github.com/Chandan-IITI/Tf-GCZSL
https://github.com/Chang-Chia-Chi/TrackNet-Badminton-Tracking-tensorflow2
https://github.com/ChangWeiTan/TS-Extrinsic-Regression
Monash University, UEA, UCR Time Series Extrinsic Regression Archive
https://github.com/ChenxiLiu-HNU/ST-LLM
https://github.com/Chonwai/Learning_BERT
Well-Read Students Learn Better: On the Importance of Pre-training Compact Models
https://github.com/ChristianMarzahl/ObjectDetection
https://github.com/CiprianAmz/Plagiarism_Detection
Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation
https://github.com/ClimbsRocks/auto_ml
https://github.com/CogComp/BenchmarkingZeroShot
Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach
https://github.com/ContinualAI/avalanche
Dark Experience for General Continual Learning: a Strong, Simple Baseline
https://github.com/CycloneBoy/PPDetectionPytorch
https://github.com/D-X-Y/GDAS
https://github.com/D-X-Y/NATS-Bench
NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size
https://github.com/D3-AI/Orion
AER: Auto-Encoder with Regression for Time Series Anomaly Detection
https://github.com/DIG-Beihang/RobustART
RobustART: Benchmarking Robustness on Architecture Design and Training Techniques
https://github.com/DInesh1234-wq/tyredataset
https://github.com/Daffan/ros_jackal
Benchmarking Reinforcement Learning Techniques for Autonomous Navigation
https://github.com/DaloroAT/first_break_picking
https://github.com/Dam930/rllab
Benchmarking Deep Reinforcement Learning for Continuous Control
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.