Synthetic Data Generation for Language Models

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21 papers in the last four weeks, up 110% on the four weeks before. 0.2% of all new papers.

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Game Theory Driven Multi-Agent Framework Mitigates Language Model Hallucination
Jul 9, 2026Runzhe Liu, Biquan Bie, Zihao Wang +7Multi-Agent LLM Systems LLM Hallucination Mitigation
1State Key Laboratory of Fine Chemicals, Frontier Science Center for Smart Materials, Dalian University of Technology, Dalian, 116024, China · 2Dalian Key Laboratory of Intelligent Chemistry, CR Belt and Road Joint Laboratory on Intelligent Chemistry and Advanced Materials of Liaoning Province, School of Chemistry, Dalian University of Technology, Dalian, 116024, China · 4Independent Researcher, Beijing 100032, China. +1
PLURAL: A Global Dataset for Value Alignment
Jul 9, 2026Dhruv Agarwal, Anya Shukla, Tanya Goyal +1LLM Alignment Cultural Alignment
Cornell University
Hallucination Self-Play: Bootstrapping Reinforced Detector via Evolved Generator
Jul 8, 2026Shiping Yang, Shining Liang, Weihao Liu +4LLM Hallucination Detection Synthetic Data Generation for Language Models
Simon Fraser University · Microsoft · Work done during an internship at Microsoft +1
Nigeria Machinery: A Low-Resource Industrial Dataset with a Domain-Grounded Reasoning Layer
Jul 8, 2026Gospel Bassey, Vincent FakiyesiNumerical Reasoning in Language Models LLM Grounding
Independent Researcher · Engineering Education Transformations Institute, College of Engineering, University of Georgia.
Selective Left-Shift: Turning Test-Time Compute and Difficulty-based Curation into Training Data for Low-Resource Code Generation
Jul 8, 2026Didula Samaraweera, Anjana Supun, Srinath PereraRL for Code Generation Code Generation
WSO2 Santa Clara, CA, USA
Demonstrating TOFFEE: A Learned System for Synthesizing Data Agent Trajectories at Scale
Jul 7, 2026Ziting Wang, Yin Li, Zuhao Yang +3LLM Agent Trajectory Synthesis LLM Agents
Nanyang Technological University Singapore · Huawei China · Industrial and Commercial Bank of China Limited, China
LongCrafter: Towards Diverse Long-Context Understanding via Evidence-Graph-Guided Instruction Synthesis
Jul 7, 2026Chenhao Yuan, Yinhao Xu, Shuwen Xu +8LLM Fine-Tuning Evidence-Grounded Generation
University of Chinese Academy of Sciences, Beijing, China · The Key Laboratory of Cognition and Decision Intelligence for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China
Formal Disco: Scalable Open-Ended Generation of Formally Verified Programs
Jul 6, 2026Gabriel Poesia, Simon Henniger, Tzu-Han Hsu +2Code Generation LLM-Based Program Synthesis
Kempner Institute, Harvard University · School of Engineering and Applied Sciences, Harvard University
Anchored Self-Play for Code Repair
Jul 3, 2026Caroline Choi, Zeyneb Kaya, Shirley Wu +3RL for Code Generation Automated Program Repair
Department of Computer Science, Stanford University, Stanford, CA, USA.
When Does Generating More Help? Disentangling Fixed-Source Synthesis from Source Expansion in Synthetic Data Scaling
Jul 2, 2026Xu Guo, Jian Tong, Zhihui Lu +1Synthetic Data Generation Language Model Scaling Laws
Shanghai AI Laboratory · Shanghai Innovation Institute · Fudan University
Self-Study Reconsidered: The Hidden Fragility of Learning from Self-Generated QA
Jun 30, 2026Ekaterina Alimaskina, Denis Shveykin, Gleb Molodtsov +3Indirect Prompt Injection Synthetic Data Generation for Language Models
BRAIn Lab · Yandex Research
Agentic-Ideation: Sample Efficient Agentic Trajectories Synthesis for Scientific Ideation Agents
Jun 30, 2026Keyu Zhao, Lingyan Kong, Fengli Xu +1Multi-Agent LLM Systems AI Agents for Scientific Discovery
Department of Electronic Engineering, Tsinghua University.
KrishokChat: A Citation-Grounded Dataset and Benchmark for Bengali Agricultural Advisory
Jun 28, 2026Khan Raiyan Ibne Reza, Omar Ibne ShahidLLM Grounding Question Answering
North South University Dhaka, Bangladesh
A French OSCE Dialogue Dataset and Controllable Virtual Patient System for Clinical Training
Jun 26, 2026Doria Bonzi, Tom Bourgeade, Fabrice Lefèvre +1Controllable Text Generation Synthetic Data Generation for Language Models
Lorraine Universit´e, CNRS, Inria, LORIA, Nancy, France · Avignon Universit´e, LIA, UPR 4128, Avignon, France
KG2Cypher: Data-Centric Pipeline for Building Enterprise Text-to-Cypher Systems
Jun 26, 2026Minjun Choi, Yerin Kim, Junghyuk Seo +3Text-to-Cypher Knowledge Graph Question Answering
Sungkyunkwan University · NAVER
EvoOptiGraph: Weakness-Driven Coevolution via Graph-Based Structural Generation for Optimization Modeling
Jun 25, 2026Qingcan Kang, Mingyang Liu, Xiaojin Fu +3LLM Fine-Tuning Synthetic Data Generation for Language Models
Huawei Noah’s Ark Lab · Department of Computer Science, City University of Hong Kong
Autodata: An agentic data scientist to create high quality synthetic data
Jun 24, 2026Ilia Kulikov, Chenxi Whitehouse, Tianhao Wu +12Synthetic Data Generation LLM Agent Self-Improvement
FAIR at Meta
Scaling LLM Knowledge Boundaries via Distribution-Optimized Synthesis
Jun 22, 2026Songze Li, Yarong Lan, Zhongpu Bo +16Synthetic Data Pretraining Knowledge Augmentation for Language Models
Zhejiang University · ZJU-Ant Group Joint Lab of Knowledge Graph · Ant Group
CLI-Universe: Towards Verifiable Task Synthesis Engine for Terminal Agents
Jun 22, 2026Zhanbo Hua, Yifan Yao, Weihao Xie +14LLM Agent Trajectory Synthesis LLM Agents
Nanjing University · StepFun · ZODA +1
Context-Aware Distillation and Ablation for Text2DSL
Jun 21, 2026Alexander V. Kozachok, Alexander M. Nazimov, Shamil G. MagomedovLLM Prompting LLM-Based Program Synthesis
MIREA – Russian Technological University, Moscow, Russian Federation · Academy of the Federal Guard Service of the Russian Federation, Oryol, Russian Federation
Generating Public Health Responses using Survey-Augmented Large Language Models
Jun 20, 2026Leonardo Marciaga, Thuyen Pham, Julia Rezvani +4Synthetic Data Augmentation Synthetic Data Generation
Illinois Institute of Technology · University of Massachusetts Amherst · Portland State University +4
CuratorKIT : Data Curation and Synthetic Data Generation for LLM Post-Training
Jun 19, 2026Soham Bhattacharjee, Karun Sharma, Vinay Kumar Sankarapu +1Training Data Curation Synthetic Data Generation for Language Models
Lexsi Labs
DataClaw0: Agentic Tailoring Multimodal Data from Raw Streams
Jun 19, 2026Cong Wan, Zeyu Guo, Zijian Cai +6Training Data Curation Synthetic Data Generation for Language Models
Xi’an Jiaotong University · University of Chinese Academy of Sciences · Shenzhen University of Advanced Technology +1
Creating Multilingual Mental Health Dialogue Datasets: Limits of Persona-Based Localization via Nationality and Language
Jun 17, 2026Yunkai Xu, Saeed AbdullahMultilingual Language Model Evaluation Depression Detection
Pennsylvania State University, United States
Efficient Financial Language Understanding via Distillation with Synthetic Data
Jun 17, 2026Wen-Fong, Huang, Edwin SimpsonFinancial Sentiment Analysis Language Model Distillation
Xavier · School of Engineering Mathematics and Technology, University of Bristol
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
State-Grounded Multi-Agent Synthetic Data Generation for Tool-Augmented LLMs
Jun 15, 2026Rahul Khedar, Eshita, Sneha Teja Sree Reddy Thondapu +10Multi-Agent LLM Systems Tool-Augmented Language Model Agents
PayPal AI
Open-SWE-Traces: Advancing Dual-Mode Multilingual Distillation for Software Engineering Agents
Jun 14, 2026Wasi Uddin Ahmad, Nikolai Ludwig, Somshubra Majumdar +1Software Engineering Agents LLM Agent Training
NVIDIA
LLM4RTL: Tool-Assisted LLM for RTL Generation
Jun 13, 2026Jing Jin, Robert Chu, Ning Yan +1Code Generation RTL Code Generation
UC Riverside · Riverside, CA, USA · Futurewei +1
Achieving Precise Text-To-Cypher Via Grounded Knowledge Graph Data Generation
Jun 12, 2026Francesco Cazzaro, Jessica Lennon, Ariadna QuattoniText-to-Cypher Synthetic Data Generation for Language Models
Universitat Politècnica de Catalunya, Barcelona, Spain

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Game Theory Driven Multi-Agent Framework Mitigates Language Model Hallucination

Runzhe Liu, Biquan Bie, Zihao Wang, Yuchao Ma+6

1State Key Laboratory of Fine Chemicals, Frontier Science Center for Smart Materials, Dalian University of Technology, Dalian, 116024, China · 2Dalian Key Laboratory of Intelligent Chemistry, CR Belt and Road Joint Laboratory on Intelligent Chemistry and Advanced Materials of Liaoning Province, School of Chemistry, Dalian University of Technology, Dalian, 116024, China · 4Independent Researcher, Beijing 100032, China.+1

Multi-Agent LLM Systems LLM Hallucination Mitigation Multi-Agent Systems Synthetic Data Generation for Language Models Large Language Model-Guided Scientific Discovery

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The application of lightweight Large Language Models in rule-based scientific domains remains severely limited by their tendency to mimic linguistic patterns rather than reproduce axiomatic reasoning, causing frequent hallucinations. Here, we show that G-Frame, an adaptive multi-agent framework integrating Bayesian and team game principles, establishes an automated closed-loop for high-quality data synthesis and model training. By forcing the internalization of domain constraints through structured reasoning, we synthesized a specialized corpus of 363,045 chains-of-thought and 199,589 question-answer pairs. The resulting 7B model OmniChem achieves performance parity with GPT 4o mini on custom benchmarks and ChemBench while exhibiting a 79.46% reduction in hallucinations relative to its base architecture. We further demonstrate the advanced capabilities of OmniChem in molecular design and synthesis planning. This work establishes a scalable paradigm utilizing adaptive multi-agents to overcome inherent reasoning deficiencies, offering a feasible pathway for accelerating knowledge discovery in specialized scientific fields.

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