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Optimization & Theory

6,829 papers (27 classified directly here)

Subtopics

Model Compression (1,785) Optimization (1,664) Efficient Computing (1,579) Theory (1,082) Neural Network Optimization (903) Evaluation (509) Loss Functions (123) Interpretability (105) Stochastic Methods (97) Regularization (77) Generalization (24) Sparse Optimization (7)

Papers per year

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Papers (including subtopics)

Monolingual Adapters for Zero-Shot Neural Machine Translation EMNLP 2020
A Streaming Approach For Efficient Batched Beam Search EMNLP 2020
An Empirical Investigation Towards Efficient Multi-Domain Language Model Pre-training EMNLP 2020
Analyzing Individual Neurons in Pre-trained Language Models EMNLP 2020
Analyzing Redundancy in Pretrained Transformer Models EMNLP 2020
Understanding the Difficulty of Training Transformers EMNLP 2020
Adversarial Self-Supervised Data-Free Distillation for Text Classification EMNLP 2020
MOCHA: A Dataset for Training and Evaluating Generative Reading Comprehension Metrics EMNLP 2020
What Do Position Embeddings Learn? An Empirical Study of Pre-Trained Language Model Positional Encoding EMNLP 2020
Attention is Not Only a Weight: Analyzing Transformers with Vector Norms EMNLP 2020
On the Ability and Limitations of Transformers to Recognize Formal Languages EMNLP 2020
BERT-of-Theseus: Compressing BERT by Progressive Module Replacing EMNLP 2020
Vector-Vector-Matrix Architecture: A Novel Hardware-Aware Framework for Low-Latency Inference in NLP Applications EMNLP 2020
Improving Low Compute Language Modeling with In-Domain Embedding Initialisation EMNLP 2020
An information theoretic view on selecting linguistic probes EMNLP 2020
Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics EMNLP 2020
AdapterHub: A Framework for Adapting Transformers EMNLP 2020
High Performance Natural Language Processing EMNLP 2020
A Greedy Bit-flip Training Algorithm for Binarized Knowledge Graph Embeddings EMNLP 2020
Gradient-based Analysis of NLP Models is Manipulable EMNLP 2020
Dynamic Data Selection for Curriculum Learning via Ability Estimation EMNLP 2020
Pruning Redundant Mappings in Transformer Models via Spectral-Normalized Identity Prior EMNLP 2020
TopicBERT for Energy Efficient Document Classification EMNLP 2020
On the Interplay Between Fine-tuning and Sentence-level Probing for Linguistic Knowledge in Pre-trained Transformers EMNLP 2020
WER we are and WER we think we are EMNLP 2020