awesome-nlp-papers
github.com/tinh2044/awesome-nlp-papers ↗A curated collection of NLP research papers, models, datasets, and tools covering fundamentals, advanced techniques, and real-world applications. 🚀
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4. Fundamentals of Deep Learning5. Sequence Modeling6. Word Representations7. Evaluation8. Tasks9. Models10. Datasets11. NLP in Vietnamese
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9. Models
- A BERTweet-Based Design for Monitoring Behavior Change Based on Five Doors Theory on Coral Bleaching Campaign9.11 BERTweet
- Abstractive English Document Summarization Using BART Model with Chunk Method9.8 BART
- A Conspiracy Theory Text Detection Method Based on RoBERTa and XLM-RoBERTa Models9.20 XLM-RoBERTa
- ALBERT: A Lite BERT for Self-supervised Learning of Language Representations9.7 ALBERT
- ALBERT for Biomedical Named Entity Recognition9.7 ALBERT
- Analysis of Pretraining Objectives in PEGASUS9.15 PEGASUS
5. Sequence Modeling
- A Causal Framework for Explaining the Predictions of Black-Box Sequence-to-Sequence Models5.2 Sequence Models
- A critical review of RNN and LSTM variants in hydrological time series predictions5.1 RNNs and LSTMs
- Activating Self-Attention for Multi-Scene Absolute Pose Regression5.4 Transformers
- Aiatrack: Attention in Attention for Transformer Visual Tracking5.4 Transformers
- An Analysis of 'Attention' in Sequence-to-Sequence Models5.2 Sequence Models
- A review of recurrent neural networks: LSTM cells and network architectures5.1 RNNs and LSTMs
6. Word Representations
- A Comprehensive Analysis of Static Word Embeddings for Turkish6.1 Static Word Embeddings
- Analysis of Word Dependency Relations and Subword Models in Abstractive Text Summarization6.3 Subword-Based Representations
- A survey on contextual embeddings6.2 Contextualized Embeddings
- A Survey on Training and Evaluation of Word Embeddings6.1 Static Word Embeddings
- BERTRAM: Improved word embeddings have a big impact on contextualized model performance6.2 Contextualized Embeddings
- Combining contextualized embeddings and prior knowledge for clinical named entity recognition6.2 Contextualized Embeddings
8. Tasks
- A comprehensive study of named entity recognition in Chinese clinical text8.3 Named Entity Recognition (NER)
- A discourse-aware neural network-based text model for document-level text classification8.2 Text Classification
- A Feature-Based Approach to Multilingual Idiomaticity Detection8.5 Fill Mask
- A hyperintensional theory of intelligent question answering in TIL8.4 Question Answering
- An application of automated reasoning in natural language question answering8.4 Question Answering
- An introduction to a new text classification and visualization for natural language processing using topological data analysis8.2 Text Classification
7. Evaluation
- A critical analysis of metrics used for measuring progress in artificial intelligence7.1 Evaluation Metrics (Accuracy, BLEU, ROUGE, etc.)
- Adaptations of ROUGE and BLEU to better evaluate machine reading comprehension tasks7.1 Evaluation Metrics (Accuracy, BLEU, ROUGE, etc.)
- Advancing Fairness in Natural Language Processing: From Traditional Methods to Explainability7.3 Bias and Fairness Metrics
- An investigation into the validity of some metrics for automatically evaluating natural language generation systems7.1 Evaluation Metrics (Accuracy, BLEU, ROUGE, etc.)
- A survey of evaluation metrics used for NLG systems7.1 Evaluation Metrics (Accuracy, BLEU, ROUGE, etc.)
- A survey on bias and fairness in natural language processing7.3 Bias and Fairness Metrics
4. Fundamentals of Deep Learning
- Advanced metaheuristic optimization techniques in applications of deep neural networks: a review4.4 Optimization Techniques
- A Mathematical Theory of Communication4.3 Backpropagation and Gradient Descent
- An introduction to neural networks and deep learning4.1 Neural Networks and Deep Learning
- An overview of gradient descent optimization algorithms4.3 Backpropagation and Gradient Descent
- An Overview of the Activation Functions Used in Deep Learning Algorithms4.2 Activation Functions
- Application of meta-heuristic algorithms for training neural networks and deep learning architectures4.1 Neural Networks and Deep Learning
11. NLP in Vietnamese
- A Feature-Rich Vietnamese Named Entity Recognition Model11.3 Vietnamese Named Entity Recognition (NER)
- A Hybrid Approach to Vietnamese Word Segmentation Using POS Tags11.4 Vietnamese Part-of-Speech Tagging
- An Empirical Study of Maximum Entropy Approach for Part-of-Speech Tagging of Vietnamese Texts11.4 Vietnamese Part-of-Speech Tagging
- An Empirical Study on POS Tagging for Vietnamese Social Media Text11.4 Vietnamese Part-of-Speech Tagging
- An Experimental Study on Constituency Parsing for Vietnamese11.5 Vietnamese Syntax and Parsing
- Are LLMs Good for Low-resource Vietnamese and Other Translations?11.6 Machine Translation for Vietnamese
10. Datasets
- Automated Distractor Generation for Fill-in-the-Blank Items Using a Prompt-Based Learning Approach10.6 Machine Translation Datasets
- Benchmarking Zero-Shot Text Classification: Datasets, Evaluation and Entailment Approach10.2 Text Classification Datasets
- CLUENER2020: Fine-Grained Named Entity Recognition Dataset and Benchmark for Chinese10.3 Named Entity Recognition Datasets
- CommonGen: A Constrained Text Generation Challenge for Generative Commonsense Reasoning10.1 Text Generation Datasets
- Creating a Dataset for Named Entity Recognition in the Archaeology Domain10.3 Named Entity Recognition Datasets
- Crosslingual Named Entity Recognition for Clinical De-Identification Applied to a COVID-19 Italian Dataset10.3 Named Entity Recognition Datasets
Showing a sample of 428 resources. View the full list on GitHub →