← Application Areas
Machine Learning › Application Areas ›

Knowledge Distillation

2907 directly classified papers

Papers per year

Papers

UniADS: Universal Architecture-Distiller Search for Distillation Gap AAAI 2024
AIST AIRC Systems for the WMT 2024 Shared Tasks EMNLP 2024
Cooperative Knowledge Distillation: A Learner Agnostic Approach AAAI 2024
eTag: Class-Incremental Learning via Embedding Distillation and Task-Oriented Generation AAAI 2024
Data Shunt: Collaboration of Small and Large Models for Lower Costs and Better Performance AAAI 2024
MIND: Multi-Task Incremental Network Distillation AAAI 2024
Graph Attention Network with High-Order Neighbor Information Propagation for Social Recommendation IJCAI 2024
Expediting Contrastive Language-Image Pretraining via Self-Distilled Encoders AAAI 2024
A Unified Self-Distillation Framework for Multimodal Sentiment Analysis with Uncertain Missing Modalities AAAI 2024
DistilVPR: Cross-Modal Knowledge Distillation for Visual Place Recognition AAAI 2024
Tail-STEAK: Improve Friend Recommendation for Tail Users via Self-Training Enhanced Knowledge Distillation AAAI 2024
Federated Learning via Input-Output Collaborative Distillation AAAI 2024
Progressive Distillation Based on Masked Generation Feature Method for Knowledge Graph Completion AAAI 2024
LLM vs Small Model? Large Language Model Based Text Augmentation Enhanced Personality Detection Model AAAI 2024
RadOcc: Learning Cross-Modality Occupancy Knowledge through Rendering Assisted Distillation AAAI 2024
Layer Attack Unlearning: Fast and Accurate Machine Unlearning via Layer Level Attack and Knowledge Distillation AAAI 2024
Some Like It Small: Czech Semantic Embedding Models for Industry Applications AAAI 2024
CSL: Class-Agnostic Structure-Constrained Learning for Segmentation Including the Unseen AAAI 2024
Distilling Text Style Transfer With Self-Explanation From LLMs NAACL 2024
Efficient Dataset Distillation via Minimax Diffusion CVPR 2024
Reducing hallucination in structured outputs via Retrieval-Augmented Generation NAACL 2024
The Mamba in the Llama: Distilling and Accelerating Hybrid Models NIPS 2024
AutoGPT+P: Affordance-based Task Planning using Large Language Models RSS 2024
Omnipotent Distillation with LLMs for Weakly-Supervised Natural Language Video Localization: When Divergence Meets Consistency AAAI 2024
Turning Dust into Gold: Distilling Complex Reasoning Capabilities from LLMs by Leveraging Negative Data AAAI 2024