https://github.com/williamliujl/cmexam
공식 코드Benchmarking Large Language Models on CMExam -- A Comprehensive Chinese Medical Exam Dataset
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/williamliujl/llmrec
공식 코드LLMRec: Benchmarking Large Language Models on Recommendation Task
https://github.com/willogy-team/hand-gesture-recognition-smc2021
공식 코드Fine-grained Hand Gesture Recognition in Multi-viewpoint Hand Hygiene
https://github.com/wilsonlau-uw/Automatic-Assignment-of-Radiology-Examination
공식 코드https://github.com/winycg/HSAKD
공식 코드Hierarchical Self-supervised Augmented Knowledge Distillation
https://github.com/winycg/MCL-OKD
공식 코드Multi-view Contrastive Learning for Online Knowledge Distillation
https://github.com/winycg/cirkd
공식 코드Cross-Image Relational Knowledge Distillation for Semantic Segmentation
https://github.com/winycg/clip-kd
공식 코드https://github.com/winycg/l-mcl
공식 코드Online Knowledge Distillation via Mutual Contrastive Learning for Visual Recognition
https://github.com/winycg/mcl
공식 코드Online Knowledge Distillation via Mutual Contrastive Learning for Visual Recognition
https://github.com/winycg/self-kd-lib
공식 코드MixSKD: Self-Knowledge Distillation from Mixup for Image Recognition
https://github.com/winzhengkong/fedhpd
공식 코드FedHPD: Heterogeneous Federated Reinforcement Learning via Policy Distillation
https://github.com/wishever/mmidr
공식 코드https://github.com/witcherleo/knowing-how-knowing-that
공식 코드Knowing-how & Knowing-that: A New Task for Machine Comprehension of User Manuals
https://github.com/wlchen0206/llm-sp
공식 코드https://github.com/wm-bupt/oracle-mnist
공식 코드Oracle-MNIST: a Realistic Image Dataset for Benchmarking Machine Learning Algorithms
https://github.com/wmdataphys/Deep_hpDIRC
공식 코드Generative Models for Fast Simulation of Cherenkov Detectors at the Electron-Ion Collider
https://github.com/wnn2000/fednoro
공식 코드https://github.com/wnstlr/SMERF
공식 코드https://github.com/wollf2008/IKD-MIL
공식 코드https://github.com/wollf2008/fw-rd
공식 코드Whole-slide-imaging Cancer Metastases Detection and Localization with Limited Tumorous Data
https://github.com/wonchulSon/DGKD
공식 코드Densely Guided Knowledge Distillation using Multiple Teacher Assistants
https://github.com/woriazzc/kds
공식 코드Preference-Consistent Knowledge Distillation for Recommender System
https://github.com/woxihuanjiangguo/hydra-mdp
공식 코드Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillation
https://github.com/wph6/fhbench
공식 코드FHBench: Towards Efficient and Personalized Federated Learning for Multimodal Healthcare
https://github.com/wqyin/smplest-x
공식 코드SMPLest-X: Ultimate Scaling for Expressive Human Pose and Shape Estimation
https://github.com/wrinklexuan/graph-flow
공식 코드Graph Flow: Cross-layer Graph Flow Distillation for Dual Efficient Medical Image Segmentation
https://github.com/wskbest/mfc-bench
공식 코드MFC-Bench: Benchmarking Multimodal Fact-Checking with Large Vision-Language Models
https://github.com/wtl52656/imputation_benchmark
공식 코드An Experimental Evaluation of Imputation Models for Spatial-Temporal Traffic Data
https://github.com/wujiangxu/slmrec
공식 코드SLMRec: Distilling Large Language Models into Small for Sequential Recommendation
https://github.com/wujunjie1998/ref-long
공식 코드Ref-Long: Benchmarking the Long-context Referencing Capability of Long-context Language Models
https://github.com/wusiwei0410/scimmir
공식 코드SciMMIR: Benchmarking Scientific Multi-modal Information Retrieval
https://github.com/wutaiqiang/WID-NAACL2024
공식 코드Weight-Inherited Distillation for Task-Agnostic BERT Compression
https://github.com/wutaiqiang/llm_kd_akl
공식 코드Rethinking Kullback-Leibler Divergence in Knowledge Distillation for Large Language Models
https://github.com/wuyongjiancode/attriprompter
공식 코드https://github.com/wuyou3474/AVTrack
공식 코드Learning an Adaptive and View-Invariant Vision Transformer for Real-Time UAV Tracking
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.