Papers with Code 아카이브

Knowledge Distillation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

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/IDSIA/crepo

공식 코드

CREPO: An Open Repository to Benchmark Credal Network Algorithms

https://github.com/IDT-ITI/Adv-XAI-Deepfakes

공식 코드

Improving the Perturbation-Based Explanation of Deepfake Detectors Through the Use of Adversarially-Generated Samples

https://github.com/IMSY-DKFZ/probability-of-false-claims

공식 코드

False Promises in Medical Imaging AI? Assessing Validity of Outperformance Claims

https://github.com/IOHprofiler/IOHAnalyzer

공식 코드

IOHanalyzer: Detailed Performance Analyses for Iterative Optimization Heuristics

https://github.com/IOHprofiler/IOHalgorithm

공식 코드

Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler

https://github.com/IRVLUTD/SceneReplica

공식 코드

SCENEREPLICA: Benchmarking Real-World Robot Manipulation by Creating Replicable Scenes

https://github.com/IST-DASLab/KDVR

공식 코드

Knowledge Distillation Performs Partial Variance Reduction

https://github.com/IllusoryVQA/IllusoryVQA

공식 코드

Illusory VQA: Benchmarking and Enhancing Multimodal Models on Visual Illusions

https://github.com/IlyaTrofimov/MF_NAS_KD

공식 코드

Multi-fidelity Neural Architecture Search with Knowledge Distillation

https://github.com/InfLoop111/DCA

공식 코드

DCA: Dividing and Conquering Amnesia in Incremental Object Detection

https://github.com/Intelli-Chip-Lab/snn_temporal_decoupling_distillation

공식 코드

Efficient Logit-based Knowledge Distillation of Deep Spiking Neural Networks for Full-Range Timestep Deployment

https://github.com/IrvingMeng/LCE

공식 코드

Learning Compatible Embeddings

https://github.com/IvLabs/stagewise-knowledge-distillation

공식 코드

Data Efficient Stagewise Knowledge Distillation

https://github.com/JDAI-CV/fast-reid

공식 코드

Semi-Supervised Domain Generalizable Person Re-Identification

https://github.com/JHU-CLSP/AnaloBench

공식 코드

AnaloBench: Benchmarking the Identification of Abstract and Long-context Analogies

https://github.com/JHU-CLSP/CLAIMCHECK

공식 코드

CLAIMCHECK: How Grounded are LLM Critiques of Scientific Papers?

https://github.com/JHU-CLSP/NeoCoder

공식 코드

Benchmarking Language Model Creativity: A Case Study on Code Generation

https://github.com/JackqqWang/fedhelp

공식 코드

Asymmetrical Reciprocity-based Federated Learning for Resolving Disparities in Medical Diagnosis

https://github.com/James-Yip/QuantiDCE

공식 코드

Towards Quantifiable Dialogue Coherence Evaluation

https://github.com/Jangho-Kim/FFL-pytorch

공식 코드

Feature Fusion for Online Mutual Knowledge Distillation

https://github.com/Javiery3889/AttackSeqBench

공식 코드

AttackSeqBench: Benchmarking Large Language Models' Understanding of Sequential Patterns in Cyber Attacks

https://github.com/JeanKaddour/WASAM

공식 코드

When Do Flat Minima Optimizers Work?

https://github.com/JetRunner/BERT-of-Theseus

공식 코드

BERT-of-Theseus: Compressing BERT by Progressive Module Replacing

https://github.com/JetRunner/MetaDistil

공식 코드

BERT Learns to Teach: Knowledge Distillation with Meta Learning

https://github.com/Jia-Research-Lab/MSAD

공식 코드

Multi-Scale Aligned Distillation for Low-Resolution Detection

https://github.com/Jia-Research-Lab/ReviewKD

공식 코드

Distilling Knowledge via Knowledge Review

https://github.com/Jiang-Yidi/TransformerDistillation-SLU

공식 코드

Knowledge Distillation from BERT Transformer to Speech Transformer for Intent Classification

https://github.com/JinYu1998/DTKD

공식 코드

Dynamic Temperature Knowledge Distillation

https://github.com/Jingkang50/OpenPSG

공식 코드

Panoptic Scene Graph Generation

https://github.com/Jingyu6/speculative_prefill

공식 코드

Speculative Prefill: Turbocharging TTFT with Lightweight and Training-Free Token Importance Estimation

https://github.com/Joe-Hall-Lee/PSN-IRT

공식 코드

Lost in Benchmarks? Rethinking Large Language Model Benchmarking with Item Response Theory

https://github.com/JosephKJ/iOD

공식 코드

Incremental Object Detection via Meta-Learning

https://github.com/JunjH/Boosting-Light-Weight-Depth-Estimation

공식 코드

Boosting Light-Weight Depth Estimation Via Knowledge Distillation

https://github.com/JunjH/light-weight-depth-estimation

공식 코드

Boosting Light-Weight Depth Estimation Via Knowledge Distillation

https://github.com/JunlinHan/CWR

공식 코드

Underwater Image Restoration via Contrastive Learning and a Real-world Dataset

https://github.com/KB-Ding/Multi-stage-Distillaton-Framework

공식 코드

Multi-stage Distillation Framework for Cross-Lingual Semantic Similarity Matching

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