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model compression

3283 papers

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MC

Co-occurring keywords

knowledge distillation (3680) large language model (12755) neural network (6616) efficient computing (779) neural network optimization (1293) transfer learning (5442) convolutional neural network (4216) neural network pruning (265) language model (4573) parameter efficiency (415)

Papers

MSCFFN: A New FFN with Multi-Space Cross to Accelerate Transformer EMNLP 2023
Evaluating Parameter-Efficient Finetuning Approaches for Pre-trained Models on the Financial Domain EMNLP 2023
Itri Amigos at ArAIEval Shared Task: Transformer vs. Compression-Based Models for Persuasion Techniques and Disinformation Detection EMNLP 2023
Automated Knowledge Distillation via Monte Carlo Tree Search ICCV 2023
Lifting the Curse of Capacity Gap in Distilling Language Models ACL 2023
CSTAR: Towards Compact and Structured Deep Neural Networks with Adversarial Robustness AAAI 2023
ORC: Network Group-based Knowledge Distillation using Online Role Change ICCV 2023
Can We Find Strong Lottery Tickets in Generative Models? AAAI 2023
EELBERT: Tiny Models through Dynamic Embeddings EMNLP 2023
Multi-teacher Distillation for Multilingual Spelling Correction EMNLP 2023
Towards Higher Ranks via Adversarial Weight Pruning NIPS 2023
Multiplication-Free Transformer Training via Piecewise Affine Operations NIPS 2023
A Comparative Analysis of Task-Agnostic Distillation Methods for Compressing Transformer Language Models EMNLP 2023
Are Compressed Language Models Less Subgroup Robust? EMNLP 2023
Enhancing Computation Efficiency in Large Language Models through Weight and Activation Quantization EMNLP 2023
A Frustratingly Easy Post-Training Quantization Scheme for LLMs EMNLP 2023
Text Representation Distillation via Information Bottleneck Principle EMNLP 2023
The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter NIPS 2023
DIME-FM : DIstilling Multimodal and Efficient Foundation Models ICCV 2023
IMF: Integrating Matched Features Using Attentive Logit in Knowledge Distillation IJCAI 2023
Conditional Adapters: Parameter-efficient Transfer Learning with Fast Inference NIPS 2023
Progressive Ensemble Distillation: Building Ensembles for Efficient Inference NIPS 2023
SPDF: Sparse Pre-training and Dense Fine-tuning for Large Language Models UAI 2023
BiMatting: Efficient Video Matting via Binarization NIPS 2023
MixFormerV2: Efficient Fully Transformer Tracking NIPS 2023