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awesome-few-shot-learning-in-nlp
A curated list of few-shot learning in NLP. :-)
https://github.com/zhjohnchan/awesome-few-shot-learning-in-nlp
Last synced: 4 days ago
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Papers
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Research Paper
- Memory, Show the Way: Memory Based Few Shot Word Representation Learning
- Few-Shot and Zero-Shot Multi-Label Learning for Structured Label Spaces
- FewRel: A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluation
- Diverse Few-Shot Text Classification with Multiple Metrics
- Few-Shot Charge Prediction with Discriminative Legal Attributes
- Multi-Level Matching and Aggregation Network for Few-Shot Relation Classification
- Few-Shot Representation Learning for Out-Of-Vocabulary Words
- Give It a Shot: Few-shot Learning to Normalize ADR Mentions in Social Media Posts
- Hierarchical Attention Prototypical Networks for Few-Shot Text Classification
- Adapting Meta Knowledge Graph Information for Multi-Hop Reasoning over Few-Shot Relations
- Induction Networks for Few-Shot Text Classification
- Meta Relational Learning for Few-Shot Link Prediction in Knowledge Graphs
- FewRel 2.0: Towards More Challenging Few-Shot Relation Classification
- A Closer Look At Feature Space Data Augmentation For Few-Shot Intent Classification
- Bad Form: Comparing Context-Based and Form-Based Few-Shot Learning in Distributional Semantic Models
- Few-Shot and Zero-Shot Learning for Historical Text Normalization
- Span-ConveRT: Few-shot Span Extraction for Dialog with Pretrained Conversational Representations
- Few-Shot NLG with Pre-Trained Language Model
- Dynamic Memory Induction Networks for Few-Shot Text Classification
- Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection Network
- Shaping Visual Representations with Language for Few-Shot Classification
- Learning to Customize Model Structures for Few-shot Dialogue Generation Tasks
- Meta-Learning for Few-Shot NMT Adaptation
- Extensively Matching for Few-shot Learning Event Detection
- Self-Supervised Meta-Learning for Few-Shot Natural Language Classification Tasks
- Adaptive Attentional Network for Few-Shot Knowledge Graph Completion
- Few-Shot Learning for Opinion Summarization
- Structural Supervision Improves Few-Shot Learning and Syntactic Generalization in Neural Language Models
- Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference
- Few-Shot Complex Knowledge Base Question Answering via Meta Reinforcement Learning
- Simple and Effective Few-Shot Named Entity Recognition with Structured Nearest Neighbor Learning
- Universal Natural Language Processing with Limited Annotations: Try Few-shot Textual Entailment as a Start
- Few-shot Natural Language Generation for Task-Oriented Dialog
- Few-Shot Multi-Hop Relation Reasoning over Knowledge Bases
- Dynamic Semantic Matching and Aggregation Network for Few-shot Intent Detection
- Composed Variational Natural Language Generation for Few-shot Intents
- Contract Discovery: Dataset and a Few-Shot Semantic Retrieval Challenge with Competitive Baselines
- Learning to Learn to Disambiguate: Meta-Learning for Few-Shot Word Sense Disambiguation
- COVID-19 Surveillance through Twitter using Self-Supervised and Few Shot Learning
- Effective Few-Shot Classification with Transfer Learning
- Meta-Information Guided Meta-Learning for Few-Shot Relation Classification
- A Two-phase Prototypical Network Model for Incremental Few-shot Relation Classification
- TableGPT: Few-shot Table-to-Text Generation with Table Structure Reconstruction and Content Matching
- Emergent Communication Pretraining for Few-Shot Machine Translation
- Few-shot Pseudo-Labeling for Intent Detection
- Learning to Few-Shot Learn Across Diverse Natural Language Classification Tasks
- Few-Shot Text Classification with Edge-Labeling Graph Neural Network-Based Prototypical Network
- ManyEnt: A Dataset for Few-shot Entity Typing
- Automatically Identifying Words That Can Serve as Labels for Few-Shot Text Classification
- Flight of the PEGASUS? Comparing Transformers on Few-shot and Zero-shot Multi-document Abstractive Summarization
- Learning to Decouple Relations: Few-Shot Relation Classification with Entity-Guided Attention and Confusion-Aware Training
- Bridging Text and Knowledge with Multi-Prototype Embedding for Few-Shot Relational Triple Extraction
- AugNLG: Few-shot Natural Language Generation using Self-trained Data Augmentation
- Few-Shot Question Answering by Pretraining Span Selection
- Few-NERD: A Few-shot Named Entity Recognition Dataset
- TextSETTR: Few-Shot Text Style Extraction and Tunable Targeted Restyling
- Making Pre-trained Language Models Better Few-shot Learners
- Lexicon Learning for Few Shot Sequence Modeling
- Few-Shot Text Ranking with Meta Adapted Synthetic Weak Supervision
- A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters
- Learning from Miscellaneous Other-Class Words for Few-shot Named Entity Recognition
- Multi-Label Few-Shot Learning for Aspect Category Detection
- On Training Instance Selection for Few-Shot Neural Text Generation
- Distinct Label Representations for Few-Shot Text Classification
- Entity Concept-enhanced Few-shot Relation Extraction
- Meta-Learning for Few-Shot Named Entity Recognition
- Semi-supervised Meta-learning for Cross-domain Few-shot Intent Classification
- Improving Zero and Few-Shot Abstractive Summarization with Intermediate Fine-tuning and Data Augmentation
- Few-shot Intent Classification and Slot Filling with Retrieved Examples
- DReCa: A General Task Augmentation Strategy for Few-Shot Natural Language Inference
- Incremental Few-shot Text Classification with Multi-round New Classes: Formulation, Dataset and System
- Non-Parametric Few-Shot Learning for Word Sense Disambiguation
- Towards Few-shot Fact-Checking via Perplexity
- Knowledge Guided Metric Learning for Few-Shot Text Classification
- ConVEx: Data-Efficient and Few-Shot Slot Labeling
- Few-Shot Text Classification with Triplet Networks, Data Augmentation, and Curriculum Learning
- Scalable Few-Shot Learning of Robust Biomedical Name Representations
- Exploiting Cloze-Questions for Few-Shot Text Classification and Natural Language Inference
- Self-Training Pre-Trained Language Models for Zero- and Few-Shot Multi-Dialectal Arabic Sequence Labeling
- A Neural Few-Shot Text Classification Reality Check
- Few-shot learning through contextual data augmentation
- Few-Shot Semantic Parsing for New Predicates
- Few-shot Learning for Slot Tagging with Attentive Relational Network
- Few Shot Dialogue State Tracking using Meta-learning
- Exploring the Limits of Few-Shot Link Prediction in Knowledge Graphs
- Story Centaur: Large Language Model Few Shot Learning as a Creative Writing Tool
- Few-Shot Learning of an Interleaved Text Summarization Model by Pretraining with Synthetic Data
- Few-Shot Event Detection with Prototypical Amortized Conditional Random Field
- Frustratingly Simple Few-Shot Slot Tagging
- UserAdapter: Few-Shot User Learning in Sentiment Analysis
- Few-shot Knowledge Graph-to-Text Generation with Pretrained Language Models
- Meta-Learning Adversarial Domain Adaptation Network for Few-Shot Text Classification
- Bi-Granularity Contrastive Learning for Post-Training in Few-Shot Scene
- Adaptive Knowledge-Enhanced Bayesian Meta-Learning for Few-shot Event Detection
- Enhancing Zero-shot and Few-shot Stance Detection with Commonsense Knowledge Graph
- Learning to Bridge Metric Spaces: Few-shot Joint Learning of Intent Detection and Slot Filling
- Few-Shot Upsampling for Protest Size Detection
- Reordering Examples Helps during Priming-based Few-Shot Learning
- Don’t Miss the Labels: Label-semantic Augmented Meta-Learner for Few-Shot Text Classification
- It’s Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners
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