awesome-nlp-references
github.com/judepark96/awesome-nlp-references ↗A curated list of resources dedicated to Knowledge Distillation, Recommendation System, especially Natural Language Processing (NLP).
33
GitHub Stars
59
Curated Resources
19
Categories
1 day ago
Last Refreshed
RetrievalLanguage ModelConversational AgentsPre-ProcessingGraph Neural NetworkRecommendation SystemKnowledge DistillationMeta LearningNamed Entity RecognitionMetric LearningData ArgumentationSequence LabelingKeyphrase Extraction/GenerationRelation ExtractionMachine TranslationEvaluation MetricTutorialToolContributors
Use this list with your AI agent
Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me pre-processing resources from awesome-nlp-references"
Installation instructions →What's inside
Language Model
- A Generative Model for Joint Natural Language Understanding and Generation
- An Efficient Framework for Learning Sentence Representations
- A new model and dataset for long-range memory
- A Primer in BERTology: What we know about how BERT works
- Contextualized Non-local Neural Networks for Sequence Learning
- DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference
Knowledge Distillation
- Attentive Student Meets Multi-Task Teacher: Improved Knowledge Distillation for Pretrained Models
- Distilling Task-Specific Knowledge from BERT into Simple Neural Networks
- Distilling Transformers into Simple Neural Networks with Unlabeled Transfer Data
- Robust Language Representation Learning via Multi-task Knowledge Distillation
- Understanding Knowledge Distillation in Neural Sequence Generation
Metric Learning
- BERTScore: Evaluating Text Generation with BERT
- Better Automatic Evaluation of Open-Domain Dialogue Systems with Contextualized Embeddings
- Deep Metric Learning using Similarities from Nonlinear Rank Approximations
- Instance Cross Entropy for Deep Metric Learning
- Keyword-Attentive Deep Semantic Matching
- Matching Embeddings for Domain Adaptation
Data Argumentation
Tutorial
Conversational Agents
- Deep Generative Models with Learnable Knowledge Constraints
- Explaination in Korean by PingPong Team
- Neural Text Generation from Rich Semantic Representations
- Pretraining Methods for Dialog Context Representation Learning
- Self-Supervised Dialogue Learning
- Sequential Attention-based Network for Noetic End-to-End Response Selection
Showing a sample of 59 resources. View the full list on GitHub →