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
16 hours 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 →