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Methodology
← Learning Types
Machine Learning
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Knowledge Distillation
503 directly classified papers
Papers per year
2017: 3
2018: 7
2019: 12
2020: 26
2021: 54
2022: 72
2023: 81
2024: 118
2025: 129
2026: 1
Papers
Federated Learning via Input-Output Collaborative Distillation
AAAI 2024
Bootstrapping Chest CT Image Understanding by Distilling Knowledge from X-ray Expert Models
CVPR 2024
Ranking Distillation for Open-Ended Video Question Answering with Insufficient Labels
CVPR 2024
PELA: Learning Parameter-Efficient Models with Low-Rank Approximation
CVPR 2024
Event Stream-based Visual Object Tracking: A High-Resolution Benchmark Dataset and A Novel Baseline
CVPR 2024
Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-Free Continual Learning
WACV 2024
Complementary Knowledge Distillation for Robust and Privacy-Preserving Model Serving in Vertical Federated Learning
AAAI 2024
D^4: Dataset Distillation via Disentangled Diffusion Model
CVPR 2024
Generalized Large-Scale Data Condensation via Various Backbone and Statistical Matching
CVPR 2024
UDON: Universal Dynamic Online distillatioN for generic image representations
NIPS 2024
Plug-and-Play Diffusion Distillation
CVPR 2024
Over-parameterized Student Model via Tensor Decomposition Boosted Knowledge Distillation
NIPS 2024
SimDistill: Simulated Multi-Modal Distillation for BEV 3D Object Detection
AAAI 2024
From Instance Training to Instruction Learning: Task Adapters Generation from Instructions
NIPS 2024
Discrepancy and Uncertainty Aware Denoising Knowledge Distillation for Zero-Shot Cross-Lingual Named Entity Recognition
AAAI 2024
From Coarse to Fine: A Distillation Method for Fine-Grained Emotion-Causal Span Pair Extraction in Conversation
AAAI 2024
On Giant's Shoulders: Effortless Weak to Strong by Dynamic Logits Fusion
NIPS 2024
Flipped Classroom: Aligning Teacher Attention with Student in Generalized Category Discovery
NIPS 2024
Self-Distillation Bridges Distribution Gap in Language Model Fine-Tuning
ACL 2024
KNN-Instruct: Automatic Instruction Construction with K Nearest Neighbor Deduction
EMNLP 2024
Induced Model Matching: Restricted Models Help Train Full-Featured Models
NIPS 2024
Rethinking Reverse Distillation for Multi-Modal Anomaly Detection
AAAI 2024
Layer Attack Unlearning: Fast and Accurate Machine Unlearning via Layer Level Attack and Knowledge Distillation
AAAI 2024
Decomposed Cross-Modal Distillation for RGB-Based Temporal Action Detection
CVPR 2023
Adaptive Data-Free Quantization
CVPR 2023
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