DualMix: Unleashing the Potential of Data Augmentation for Online Class-Incremental Learning
Paper
• 2303.07864 • Published
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Data augmentation
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Self-Evolution Learning for Mixup: Enhance Data Augmentation on Few-Shot Text Classification Tasks
Paper • 2305.13547 • Published • 1 -
MixPro: Simple yet Effective Data Augmentation for Prompt-based Learning
Paper • 2304.09402 • Published • 2 -
LM-CPPF: Paraphrasing-Guided Data Augmentation for Contrastive Prompt-Based Few-Shot Fine-Tuning
Paper • 2305.18169 • Published • 1 -
Effectiveness of Data Augmentation for Parameter Efficient Tuning with Limited Data
Paper • 2303.02577 • Published • 1 -
Augmentation with Projection: Towards an Effective and Efficient Data Augmentation Paradigm for Distillation
Paper • 2210.11768 • Published • 1 -
TreeMix: Compositional Constituency-based Data Augmentation for Natural Language Understanding
Paper • 2205.06153 • Published • 1 -
Syntax-driven Data Augmentation for Named Entity Recognition
Paper • 2208.06957 • Published • 1 -
Robust Self-Augmentation for Named Entity Recognition with Meta Reweighting
Paper • 2204.11406 • Published • 1 -
Distributional Data Augmentation Methods for Low Resource Language
Paper • 2309.04862 • Published • 1 -
Data Augmentation in Natural Language Processing: A Novel Text Generation Approach for Long and Short Text Classifiers
Paper • 2103.14453 • Published • 1 -
TTIDA: Controllable Generative Data Augmentation via Text-to-Text and Text-to-Image Models
Paper • 2304.08821 • Published • 1 -
Toward Understanding Generative Data Augmentation
Paper • 2305.17476 • Published • 1 -
Guiding Generative Language Models for Data Augmentation in Few-Shot Text Classification
Paper • 2111.09064 • Published • 1 -
AttentionMix: Data augmentation method that relies on BERT attention mechanism
Paper • 2309.11104 • Published • 1 -
Data Augmentation Approaches in Natural Language Processing: A Survey
Paper • 2110.01852 • Published • 1 -
Understanding the Role of Mixup in Knowledge Distillation: An Empirical Study
Paper • 2211.03946 • Published • 1 -
What Makes a "Good" Data Augmentation in Knowledge Distillation -- A Statistical Perspective
Paper • 2012.02909 • Published • 1 -
HARD: Hard Augmentations for Robust Distillation
Paper • 2305.14890 • Published • 1 -
Large Language Models as Annotators: Enhancing Generalization of NLP Models at Minimal Cost
Paper • 2306.15766 • Published • 1 -
Scaling Relationship on Learning Mathematical Reasoning with Large Language Models
Paper • 2308.01825 • Published • 23 -
LLM360: Towards Fully Transparent Open-Source LLMs
Paper • 2312.06550 • Published • 57 -
When Chosen Wisely, More Data Is What You Need: A Universal Sample-Efficient Strategy For Data Augmentation
Paper • 2203.09391 • Published • 1 -
Post Hoc Explanations of Language Models Can Improve Language Models
Paper • 2305.11426 • Published • 1 -
Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling
Paper • 2401.16380 • Published • 51 -
CooK: Empowering General-Purpose Language Models with Modular and Collaborative Knowledge
Paper • 2305.09955 • Published • 1 -
Augmenting Math Word Problems via Iterative Question Composing
Paper • 2401.09003 • Published • 2 -
Pre-trained Language Models as Re-Annotators
Paper • 2205.05368 • Published • 1 -
LLM2LLM: Boosting LLMs with Novel Iterative Data Enhancement
Paper • 2403.15042 • Published • 27 -
Learning to Generate Instruction Tuning Datasets for Zero-Shot Task Adaptation
Paper • 2402.18334 • Published • 12 -
Automated Data Curation for Robust Language Model Fine-Tuning
Paper • 2403.12776 • Published -
MuMath-Code: Combining Tool-Use Large Language Models with Multi-perspective Data Augmentation for Mathematical Reasoning
Paper • 2405.07551 • Published -
Empowering Large Language Models for Textual Data Augmentation
Paper • 2404.17642 • Published -
CoDa: Constrained Generation based Data Augmentation for Low-Resource NLP
Paper • 2404.00415 • Published -
Enhancing Conversational Search: Large Language Model-Aided Informative Query Rewriting
Paper • 2310.09716 • Published -
Deterministic Reversible Data Augmentation for Neural Machine Translation
Paper • 2406.02517 • Published -
AdaCQR: Enhancing Query Reformulation for Conversational Search via Sparse and Dense Retrieval Alignment
Paper • 2407.01965 • Published -
Adaptive Query Rewriting: Aligning Rewriters through Marginal Probability of Conversational Answers
Paper • 2406.10991 • Published • 1 -
Conversational Query Reformulation with the Guidance of Retrieved Documents
Paper • 2407.12363 • Published