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Data Augmentation
3622 directly classified papers
Papers per year
2002: 2
2006: 1
2008: 2
2009: 1
2011: 3
2012: 3
2013: 9
2014: 8
2015: 7
2016: 35
2017: 45
2018: 108
2019: 239
2020: 329
2021: 477
2022: 518
2023: 607
2024: 561
2025: 546
2026: 121
Papers
German Text Simplification: Finetuning Large Language Models with Semi-Synthetic Data
EACL 2024
Surveying the FAIRness of Annotation Tools: Difficult to find, difficult to reuse
EACL 2024
Compilation of a Synthetic Judeo-French Corpus
EACL 2024
Exploring the impact of noise in low-resource ASR for Tamil
EACL 2024
Complex question generation using discourse-based data augmentation
EACL 2024
MasonPerplexity at ClimateActivism 2024: Integrating Advanced Ensemble Techniques and Data Augmentation for Climate Activism Stance and Hate Event Identification
EACL 2024
Towards Accurate and Fair Cognitive Diagnosis via Monotonic Data Augmentation
NIPS 2024
Relevance-aware Diverse Query Generation for Out-of-domain Text Ranking
ACL 2024
The ALCHEmist: Automated Labeling 500x CHEaper than LLM Data Annotators
NIPS 2024
Multi-News+: Cost-efficient Dataset Cleansing via LLM-based Data Annotation
EMNLP 2024
Temporal Validity Change Prediction
ACL 2024
Fine-grained Control of Generative Data Augmentation in IoT Sensing
NIPS 2024
MuMath-Code: Combining Tool-Use Large Language Models with Multi-perspective Data Augmentation for Mathematical Reasoning
EMNLP 2024
BIGOS V2 Benchmark for Polish ASR: Curated Datasets and Tools for Reproducible Evaluation
NIPS 2024
DialogCC: An Automated Pipeline for Creating High-Quality Multi-Modal Dialogue Dataset
NAACL 2024
TüDuo at SemEval-2024 Task 2: Flan-T5 and Data Augmentation for Biomedical NLI
NAACL 2024
MALTO at SemEval-2024 Task 6: Leveraging Synthetic Data for LLM Hallucination Detection
NAACL 2024
Enhancing Dialogue State Tracking Models through LLM-backed User-Agents Simulation
ACL 2024
Byun at SemEval-2024 Task 6: Text Classification on Hallucinating Text with Simple Data Augmentation
NAACL 2024
Masked Thought: Simply Masking Partial Reasoning Steps Can Improve Mathematical Reasoning Learning of Language Models
ACL 2024
Synthesize, Partition, then Adapt: Eliciting Diverse Samples from Foundation Models
NIPS 2024
CYUT at SemEval-2024 Task 7: A Numerals Augmentation and Feature Enhancement Approach to Numeral Reading Comprehension
NAACL 2024
Getting Sick After Seeing a Doctor? Diagnosing and Mitigating Knowledge Conflicts in Event Temporal Reasoning
NAACL 2024
WaveCoder: Widespread And Versatile Enhancement For Code Large Language Models By Instruction Tuning
ACL 2024
UnibucLLM: Harnessing LLMs for Automated Prediction of Item Difficulty and Response Time for Multiple-Choice Questions
NAACL 2024
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