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Text Augmentation

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You can read these blog posts to get an overview of the approaches.

A Visual Survey of Data Augmentation in NLP

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/AtmaHou/Seq2SeqDataAugmentationForLU

공식 코드

Sequence-to-Sequence Data Augmentation for Dialogue Language Understanding

https://github.com/BUTSpeechFIT/BrnoLM

공식 코드

Text Augmentation for Language Models in High Error Recognition Scenario

https://github.com/DLYuanGod/RPN

공식 코드

RPN: A Word Vector Level Data Augmentation Algorithm in Deep Learning for Language Understanding

https://github.com/HazyResearch/tanda

공식 코드

Learning to Compose Domain-Specific Transformations for Data Augmentation

https://github.com/WFSRDataScience/SemEval2025Task9

공식 코드

BrightCookies at SemEval-2025 Task 9: Exploring Data Augmentation for Food Hazard Classification

https://github.com/YichaoCai1/CLAP

공식 코드

CLAP: Isolating Content from Style through Contrastive Learning with Augmented Prompts

https://github.com/ace117mc/transformer-models-covid

공식 코드

Adaptation of domain-specific transformer models with text oversampling for sentiment analysis of social media posts on Covid-19 vaccines

https://github.com/beyondguo/STA

공식 코드

Selective Text Augmentation with Word Roles for Low-Resource Text Classification

https://github.com/chris210634/mudg

공식 코드

Multimodal Unsupervised Domain Generalization by Retrieving Across the Modality Gap

https://github.com/clarin-pl/text-augumentation-with-chatgpt

공식 코드

From Big to Small Without Losing It All: Text Augmentation with ChatGPT for Efficient Sentiment Analysis

https://github.com/d-ailin/blind-faith-in-text

공식 코드

Words or Vision: Do Vision-Language Models Have Blind Faith in Text?

https://github.com/declare-lab/doublemix

공식 코드

DoubleMix: Simple Interpolation-Based Data Augmentation for Text Classification

https://github.com/dsfsi/textaugment

공식 코드

Improving short text classification through global augmentation methods

https://github.com/faiyazkhan11/ban-cap

공식 코드

BAN-Cap: A Multi-Purpose English-Bangla Image Descriptions Dataset

https://github.com/gozdesahin/crop-rotate-augment

공식 코드

Data Augmentation via Dependency Tree Morphing for Low-Resource Languages

https://github.com/hope-rita/thlm

공식 코드

Pretraining Language Models with Text-Attributed Heterogeneous Graphs

https://github.com/jaaack-wang/linguistic-knowledge-in-DA-for-NLP

공식 코드

Linguistic Knowledge in Data Augmentation for Natural Language Processing: An Example on Chinese Question Matching

https://github.com/jasonwei20/eda_nlp

공식 코드

EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks

https://github.com/kanhatakeyama/Additional-training-Llama2

공식 코드

Teaching Specific Scientific Knowledge into Large Language Models through Additional Training

https://github.com/kinit-sk/llm-div-incts

공식 코드

Effects of diversity incentives on sample diversity and downstream model performance in LLM-based text augmentation

https://github.com/kinit-sk/selec-strats-for-aug

공식 코드

Use Random Selection for Now: Investigation of Few-Shot Selection Strategies in LLM-based Text Augmentation for Classification

https://github.com/mia-yatingyu/stdd

공식 코드

Building a Multi-modal Spatiotemporal Expert for Zero-shot Action Recognition with CLIP

https://github.com/mifei/st-tod

공식 코드

Self-training Improves Pre-training for Few-shot Learning in Task-oriented Dialog Systems

https://github.com/mikewangwzhl/zemi

공식 코드

Zemi: Learning Zero-Shot Semi-Parametric Language Models from Multiple Tasks

https://github.com/mlgroup-jlu/llm-data-aug-survey

공식 코드

A Survey on Data Augmentation in Large Model Era

https://github.com/mosh98/text_aug_low_res

공식 코드

Distributional Data Augmentation Methods for Low Resource Language

https://github.com/naver-ai/hypermix

공식 코드

GPT3Mix: Leveraging Large-scale Language Models for Text Augmentation

https://github.com/pfnet-research/contextual_augmentation

공식 코드

Contextual Augmentation: Data Augmentation by Words with Paradigmatic Relations

https://github.com/snap-research/mmvid

공식 코드

Show Me What and Tell Me How: Video Synthesis via Multimodal Conditioning

https://github.com/sonlam1102/text_augmentation_vietnamese

공식 코드

Empirical Study of Text Augmentation on Social Media Text in Vietnamese

https://github.com/szu-ddj/edda

공식 코드

EDDA: A Encoder-Decoder Data Augmentation Framework for Zero-Shot Stance Detection

https://github.com/thunlp/MixADA

공식 코드

Better Robustness by More Coverage: Adversarial Training with Mixup Augmentation for Robust Fine-tuning

https://github.com/wangcongcong123/crisis-mtl

공식 코드

UCD-CS at TREC 2021 Incident Streams Track

https://github.com/wangcongcong123/sta

공식 코드

STA: Self-controlled Text Augmentation for Improving Text Classifications

https://github.com/wsuagrobotics/data-aug-multi-modal-llm

공식 코드

Image, Text, and Speech Data Augmentation using Multimodal LLMs for Deep Learning: A Survey

https://github.com/xingy038/laser

공식 코드

Laser: Efficient Language-Guided Segmentation in Neural Radiance Fields

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