Large Language Model-Based Data Augmentation

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26 papers4 papers in the last four weeks, up 33% on the four weeks before. 0.0% of all new papers.

Language Model Augmented Decision Transformer for Multi-Task Offline Reinforcement Learning
Nov 2, 2026Xinbo Zhao, Yuhang Liu, Xin Zhang +4Multi-Task RL Decision Transformer
State University of New York at Binghamton · San Diego State University · LinkedIn +1
Data Optimization for LLMs: A Survey
Oct 24, 2026Ou WuLLM Training Large Language Model-Based Data Augmentation
Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, China
LLMs as survey respondents: Comparison to simple semantic baselines
Oct 21, 2026Esko Lehtonen, Tommi Buder-GröndahlLarge Language Model-Based Data Augmentation Language Model Generation Evaluation
VTT Technical Research Centre of Finland Ltd Espoo, Finland · University of Helsinki Helsinki, Finland
Diverse Reasoning Paths Matter: Symbolic Equivalence Augmentation for Enhancing RL Exploration
Oct 15, 2026Xiaoou Liu, Tiejin Chen, Hanyang Chen +2RL for Language Model Reasoning Large Language Model-Based Data Augmentation
Arizona State University · Independent Researcher
SharP: Soft and Hard Prompt-Guided Augmentation with LLM for Low Resource Fake News Detection
Oct 9, 2026Ziyu Luo, Wei Li, Haoping Huang +2Large Language Model-Based Data Augmentation Fake News Detection
Key Laboratory of Dependable Service Computing in Cyber Physical Society (Chongqing University), Ministry of Education, Chongqing 401331, China · School of Big Data and Software Engineering, Chongqing University, Chongqing 400044, China · Department of Plastic Surgery, Chongqing University Central Hospital, Chongqing Emergency Medical Center, Chongqing 400000, China +1
Colorectal Cancer Segmentation with Adaptive Augmentation and Multi-Resolution Ensemble Models
Sep 29, 2026Ümit Mert Çağlar, Alptekin TemizelHistopathology Image Segmentation Large Language Model-Based Data Augmentation
Graduate School of Informatics, METU, Ankara, Turkey
DualGuard: Dual-Mode Quality Control for Logic-Preserving Data Augmentation
Sep 26, 2026Shenghao Li, Lin ZhaoData Augmentation Synthetic Data Augmentation
Guangzhou University, Guangzhou, China
Dictionary-Constrained Grapheme-to-Phoneme for Unsegmented Languages from LLM-Annotated Data
Sep 17, 2026Rui Hu, Zhenpeng Zhan, Xiaolong LinLarge Language Model-Based Data Augmentation G2P Conversion
Baidu Inc., Shenzhen, China
REER-PT: Reverse-Engineered Reasoning for Perplexity-Guided Pre-training Data Augmentation
Aug 31, 2026Haoran Que, Jiajun Shi, Ting Huang +7Language Model Pretraining Synthetic Data Pretraining
Peking University · ByteDance Seed · Work done at ByteDance Seed +1
TEAMMix: Taxonomy Enrichment Augmentation and Minority-augmented Mixing Strategy for LLM-enhanced Weak-Supervised Hierarchical Text Classification
Aug 11, 2026Jian Zhang, Zhuohao Yang, Songlin Lei +6Class-Imbalanced Learning Hierarchical Classification
School of Computer Science and Technology, Zhejiang University, Hangzhou, China · ZJU-UIUC Institute, Zhejiang University, Haining, China · Shaoxing K3i Technology Co. Ltd +1
Want Better Synthetic Data? Steer It: Activation Steering for Low-Resource Language Generation
Jun 16, 2026Jan Cegin, Daniil Gurgurov, Yusser Al Ghussin +1Language Model Steering Synthetic Data Generation for Language Models
Kempelen Institute of Intelligent Technologies, Bratislava, Slovakia · German Research Institute for Artificial Intelligence (DFKI), Saarbrücken, Germany
Generalistic or Specific Embeddings, Which is Better? An Empirical Study on Search for Clinical Coding in Non-English Languages
May 28, 2026David Rey-Blanco, Roberto CruzData Augmentation Healthcare
TietAI
EmbGen: Teaching with Reassembled Corpora
May 19, 2026Arun K Lenin, Kai Rouse, Andrea Nicastro +1Synthetic Instruction Generation Domain Adaptation for LLMs
Commonwealth Bank of Australia Sydney, Australia
Can Large Language Models Imitate Human Speech for Clinical Assessment? LLM-Driven Data Augmentation for Cognitive Score Prediction
May 15, 2026Si-Belkacem Yamine Ketir, Lenard Paulo Tamayo, Shohei Hisada +3Class-Imbalanced Learning Synthetic Data Augmentation
Télécom SudParis, France · Nara Institute of Science and Technology, Japan
AcquisitionSynthesis: Targeted Data Generation using Acquisition Functions
May 13, 2026Ishika Agarwal, Sofia Stoica, Emre Can Acikgoz +4Synthetic Data Generation Synthetic Data Generation for Language Models
University of Illinois Urbana-Champaign1 · Amazon2
Enhancing Online Recruitment with Category-Aware MoE and LLM-based Data Augmentation
Apr 23, 2026Minping Chen, Bing Xu, Zulong Chen +4Data Augmentation Mixture of Experts
HKUST (GZ) · Alibaba Group · Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ) +3
Enhancing Science Classroom Discourse Analysis through Joint Multi-Task Learning for Reasoning-Component Classification
Apr 22, 2026Jiho Noh, Mukhesh Raghava Katragadda, Raymond Carl +1AI in Education Multi-Task Learning
Department of Computer Science, Kennesaw State University, Kennesaw, GA 30144 USA · Bagwell College of Education, Kennesaw State University, Kennesaw, GA 30144 USA
LLM-AUG: Robust Wireless Data Augmentation with In-Context Learning in Large Language Models
Apr 20, 2026Pranshav Gajjar, Manan Tiwari, Sayanta Seth +1Distribution Shift Robustness Synthetic Data Augmentation
NextG Wireless Lab, North Carolina State University, NC
When Does Data Augmentation Help? Evaluating LLM and Back-Translation Methods for Hausa and Fongbe NLP
Apr 14, 2026Mahounan Pericles Adjovi, Roald Eiselen, Prasenjit MitraBack-Translation Synthetic Data Augmentation
Carnegie Mellon University Africa, Kigali, Rwanda · Centre for Text Technology, North-West University, Potchefstroom, South Africa
NameBERT: Scaling Name-Based Nationality Classification with LLM-Augmented Open Academic Data
Apr 12, 2026Cong Ming, Ruixin Shi, Yifan HuBidirectional Encoder Representations from Transformers Large Language Model-Based Data Augmentation
Northeastern University, United States
Translation Asymmetry in LLMs as a Data Augmentation Factor: A Case Study for 6 Romansh Language Varieties
Mar 26, 2026Jannis Vamvas, Ignacio Pérez Prat, Angela Heldstab +3Dialectal MT Machine Translation
University of Zurich · Lia Rumantscha
Synthetic Mixed Training: Scaling Parametric Knowledge Acquisition Beyond RAG
Mar 24, 2026Seungju Han, Konwoo Kim, Chanwoo Park +5Knowledge Augmentation for Language Models Synthetic Data Augmentation
Stanford University · MIT · University of Washington
SPA: A Simple but Tough-to-Beat Baseline for Knowledge Injection
Mar 23, 2026Kexian Tang, Jiani Wang, Shaowen Wang +1Knowledge Augmentation for Language Models Synthetic Data Generation for Language Models
Institute for Interdisciplinary Information Sciences, Tsinghua University
Synthetic Data Domain Adaptation for ASR via LLM-based Text and Phonetic Respelling Augmentation
Mar 11, 2026Natsuo Yamashita, Koichi Nagatsuka, Hiroaki Kokubo +2Large Language Model-Based Data Augmentation Domain Adaptation for ASR
Hitachi, Ltd.
SAIL: Similarity-Aware Guidance and Inter-Caption Augmentation-based Learning for Weakly-Supervised Dense Video Captioning
Mar 5, 2026Ye-Chan Kim, SeungJu Cha, Si-Woo Kim +3Large Language Model-Based Data Augmentation Video Captioning
Hanyang University, South Korea
Label-Consistent Data Generation for Aspect-Based Sentiment Analysis Using LLM Agents
Feb 18, 2026Mohammad H. A. Monfared, Lucie Flek, Akbar KarimiSynthetic Data Augmentation Large Language Model-Based Data Augmentation
Bonn-Aachen International Center for Information Technology, University of Bonn, Germany · Lamarr Institute for Machine Learning and Artificial Intelligence, Germany

Nov 2, 2026J/K move · Enter open · S save

Language Model Augmented Decision Transformer for Multi-Task Offline Reinforcement Learning

Xinbo Zhao, Yuhang Liu, Xin Zhang, Lei Le+3

State University of New York at Binghamton · San Diego State University · LinkedIn+1

Multi-Task RL Decision Transformer Large Language Model-Based Data Augmentation

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Offline multi-task reinforcement learning (MTRL) aims to learn a unified policy from heterogeneous offline datasets that generalizes across tasks. However, existing offline MTRL methods often struggle with two fundamental issues: severe per-task data scarcity and limited cross-task generalization. In this paper, we propose Language-Model Augmented Decision Transformer (LaMA-DT), a unified sequence-modeling framework that leverages a single large language model (LLM) for both trajectory augmentation and multi-task policy learning. LaMA-DT uses natural-language task descriptions to guide task-aligned trajectory augmentation through a set of supervised generation and alignment objectives, and incorporates a scoring-and-filtering mechanism to retain high-quality augmented trajectories. The same LLM is then repurposed as a language-conditioned Decision Transformer and fine-tuned on a mixture of real and augmented data. Experiments on Meta-World and MuJoCo multi-task benchmarks demonstrate that LaMA-DT consistently outperforms competitive baselines, particularly in low-data regimes, showing that language-guided data augmentation substantially improves cross-task generalization.