← Learning Types
Deep Learning › Learning Types ›

Knowledge Distillation

790 directly classified papers

Papers per year

Papers

Students Parrot Their Teachers: Membership Inference on Model Distillation NIPS 2023
Propagating Knowledge Updates to LMs Through Distillation NIPS 2023
Augmentation-Free Dense Contrastive Knowledge Distillation for Efficient Semantic Segmentation NIPS 2023
Beneath the Surface: Unveiling Harmful Memes with Multimodal Reasoning Distilled from Large Language Models EMNLP 2023
Learning to Learn from APIs: Black-Box Data-Free Meta-Learning ICML 2023
Leveraging Contrastive Learning and Knowledge Distillation for Incomplete Modality Rumor Detection EMNLP 2023
Learn From One Specialized Sub-Teacher: One-to-One Mapping for Feature-Based Knowledge Distillation EMNLP 2023
Cross-Modal Distillation for Speaker Recognition AAAI 2023
Learning to Imagine: Distillation-Based Interactive Context Exploitation for Dialogue State Tracking AAAI 2023
What Makes it Ok to Set a Fire? Iterative Self-distillation of Contexts and Rationales for Disambiguating Defeasible Social and Moral Situations EMNLP 2023
LLM aided semi-supervision for efficient Extractive Dialog Summarization EMNLP 2023
Data-Free Sketch-Based Image Retrieval CVPR 2023
Distilling Cross-Temporal Contexts for Continuous Sign Language Recognition CVPR 2023
ProKD: An Unsupervised Prototypical Knowledge Distillation Network for Zero-Resource Cross-Lingual Named Entity Recognition AAAI 2023
Improving Simultaneous Machine Translation with Monolingual Data AAAI 2023
Neural TSP Solver with Progressive Distillation AAAI 2023
Continual Variational Autoencoder via Continual Generative Knowledge Distillation AAAI 2023
Extracting Low-/High- Frequency Knowledge from Graph Neural Networks and Injecting It into MLPs: An Effective GNN-to-MLP Distillation Framework AAAI 2023
Adaptive Mixing of Auxiliary Losses in Supervised Learning AAAI 2023
DisGUIDE: Disagreement-Guided Data-Free Model Extraction AAAI 2023
AdapterDistillation: Non-Destructive Task Composition with Knowledge Distillation EMNLP 2023
Cache me if you Can: an Online Cost-aware Teacher-Student framework to Reduce the Calls to Large Language Models EMNLP 2023
Tailoring Instructions to Student’s Learning Levels Boosts Knowledge Distillation ACL 2023
Distilling Script Knowledge from Large Language Models for Constrained Language Planning ACL 2023
Mixture Uniform Distribution Modeling and Asymmetric Mix Distillation for Class Incremental Learning AAAI 2023