https://github.com/guojy-eatstg/alignahead
공식 코드Alignahead: Online Cross-Layer Knowledge Extraction on Graph Neural Networks
Papers with Code 아카이브
Knowledge Distillation
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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/guoleisun/indiscernible-object-counting
공식 코드https://github.com/guoyongcs/ews
공식 코드https://github.com/gusye1234/recad
공식 코드RecAD: Towards A Unified Library for Recommender Attack and Defense
https://github.com/gyguo/pixeldistillation
공식 코드Pixel Distillation: A New Knowledge Distillation Scheme for Low-Resolution Image Recognition
https://github.com/gyhou123/egosocialarena
공식 코드https://github.com/gykovacs/retina_vessel_segmentation
공식 코드https://github.com/gzyaftermath/cat-kd
공식 코드https://github.com/h-jamieu/noisy_ostracods
공식 코드https://github.com/h2xlab/CaT
공식 코드https://github.com/hadi-m-ibrahim/beyond-conventional-transformers
공식 코드https://github.com/hahamyt/mst
공식 코드MST: Adaptive Multi-Scale Tokens Guided Interactive Segmentation
https://github.com/hahnyuan/llm-viewer
공식 코드https://github.com/haiduo/deepkd
공식 코드DeepKD: A Deeply Decoupled and Denoised Knowledge Distillation Trainer
https://github.com/haihabi/learned-bcrb
공식 코드Learned Bayesian Cramér-Rao Bound for Unknown Measurement Models Using Score Neural Networks
https://github.com/haileyfamo/insqabench
공식 코드InsQABench: Benchmarking Chinese Insurance Domain Question Answering with Large Language Models
https://github.com/haiv-lab/mekd
공식 코드Aligning Logits Generatively for Principled Black-Box Knowledge Distillation
https://github.com/haksorus/gsplatloc
공식 코드https://github.com/hakuhodo-technologies/scope-rl
공식 코드Towards Assessing and Benchmarking Risk-Return Tradeoff of Off-Policy Evaluation
https://github.com/hamedhematian/importantnews
공식 코드KhabarChin: Automatic Detection of Important News in the Persian Language
https://github.com/hanjiechen/challengeclinicalqa
공식 코드Benchmarking Large Language Models on Answering and Explaining Challenging Medical Questions
https://github.com/hanjuku-kaso/awesome-offline-rl
공식 코드CORL: Research-oriented Deep Offline Reinforcement Learning Library
https://github.com/hank0626/calf
공식 코드CALF: Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning
https://github.com/hank0626/llata
공식 코드CALF: Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning
https://github.com/hannafoe/cryptanalytical-extraction
공식 코드https://github.com/hannahblo/23_performance_analysis_ml_algorithms
공식 코드Depth Functions for Partial Orders with a Descriptive Analysis of Machine Learning Algorithms
https://github.com/hannahblo/comparing_algorithms_using_ufg_depth
공식 코드Comparing Machine Learning Algorithms by Union-Free Generic Depth
https://github.com/hannahblo/posets_optimizers
공식 코드https://github.com/hannahblo/statistical_multicriteria_evaluation_of_llm-generated_text
공식 코드https://github.com/hanniewhu/remm
공식 코드REMM:Rotation-Equivariant Framework for End-to-End Multimodal Image Matching
https://github.com/hansizeng/cl-drd
공식 코드https://github.com/hansizeng/scaling-retriever
공식 코드https://github.com/hanyue1648/reft
공식 코드Reference Twice: A Simple and Unified Baseline for Few-Shot Instance Segmentation
https://github.com/hao840/ofakd
공식 코드One-for-All: Bridge the Gap Between Heterogeneous Architectures in Knowledge Distillation
https://github.com/hao840/vanillakd
공식 코드VanillaKD: Revisit the Power of Vanilla Knowledge Distillation from Small Scale to Large Scale
https://github.com/haodeqi/BenchmarkingIntentDetection
공식 코드Benchmarking Commercial Intent Detection Services with Practice-Driven Evaluations
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.