Cover Image

Scaling Synthetic Data Creation with 1,000,000,000 Personas

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ge, Tao, Chan, Xin, Wang, Xiaoyang, Yu, Dian, Mi, Haitao, Yu, Dong
Format:	Preprint
Published:	2024
Subjects:	Computation and Language Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

SkyScript-100M: 1,000,000,000 Pairs of Scripts and Shooting Scripts for Short Drama
by: Tang, Jing, et al.
Published: (2024)

OpenCharacter: Training Customizable Role-Playing LLMs with Large-Scale Synthetic Personas
by: Wang, Xiaoyang, et al.
Published: (2025)

Low-Bit Quantization Favors Undertrained LLMs: Scaling Laws for Quantized LLMs with 100T Training Tokens
by: Ouyang, Xu, et al.
Published: (2024)

Every Question Has Its Own Value: Reinforcement Learning with Explicit Human Values
by: Yu, Dian, et al.
Published: (2025)

Improving LLM General Preference Alignment via Optimistic Online Mirror Descent
by: Zhang, Yuheng, et al.
Published: (2025)

Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing
by: Tian, Ye, et al.
Published: (2024)

One Token to Fool LLM-as-a-Judge
by: Zhao, Yulai, et al.
Published: (2025)

LongWriter: Unleashing 10,000+ Word Generation from Long Context LLMs
by: Bai, Yushi, et al.
Published: (2024)

DOTS: Learning to Reason Dynamically in LLMs via Optimal Reasoning Trajectories Search
by: Yue, Murong, et al.
Published: (2024)

Towards Self-Improvement of LLMs via MCTS: Leveraging Stepwise Knowledge with Curriculum Preference Learning
by: Wang, Xiyao, et al.
Published: (2024)

R-Zero: Self-Evolving Reasoning LLM from Zero Data
by: Huang, Chengsong, et al.
Published: (2025)

Save the Good Prefix: Precise Error Penalization via Process-Supervised RL to Enhance LLM Reasoning
by: Liu, Haolin, et al.
Published: (2026)

LiteSearch: Efficacious Tree Search for LLM
by: Wang, Ante, et al.
Published: (2024)

Evolving Language Models without Labels: Majority Drives Selection, Novelty Promotes Variation
by: Zhou, Yujun, et al.
Published: (2025)

Group Distributionally Robust Optimization-Driven Reinforcement Learning for LLM Reasoning
by: Panaganti, Kishan, et al.
Published: (2026)

MobileGUI-RL: Advancing Mobile GUI Agent through Reinforcement Learning in Online Environment
by: Shi, Yucheng, et al.
Published: (2025)

Synthetic Computers at Scale for Long-Horizon Productivity Simulation
by: Ge, Tao, et al.
Published: (2026)

Dual-Uncertainty Guided Policy Learning for Multimodal Reasoning
by: Liu, Rui, et al.
Published: (2025)

Iterative Nash Policy Optimization: Aligning LLMs with General Preferences via No-Regret Learning
by: Zhang, Yuheng, et al.
Published: (2024)

Stable and Efficient Single-Rollout RL for Multimodal Reasoning
by: Liu, Rui, et al.
Published: (2025)

CDE: Curiosity-Driven Exploration for Efficient Reinforcement Learning in Large Language Models
by: Dai, Runpeng, et al.
Published: (2025)

SVD-LLM: Truncation-aware Singular Value Decomposition for Large Language Model Compression
by: Wang, Xin, et al.
Published: (2024)

Guided Self-Evolving LLMs with Minimal Human Supervision
by: Yu, Wenhao, et al.
Published: (2025)

DSDR: Dual-Scale Diversity Regularization for Exploration in LLM Reasoning
by: Wan, Zhongwei, et al.
Published: (2026)

Balancing Cost and Effectiveness of Synthetic Data Generation Strategies for LLMs
by: Chan, Yung-Chieh, et al.
Published: (2024)

BeyondWeb: Lessons from Scaling Synthetic Data for Trillion-scale Pretraining
by: DatologyAI, et al.
Published: (2025)

DualAlign: Generating Clinically Grounded Synthetic Data
by: Li, Rumeng, et al.
Published: (2025)

SIPDO: Closed-Loop Prompt Optimization via Synthetic Data Feedback
by: Yu, Yaoning, et al.
Published: (2025)

SynLexLM: Scaling Legal LLMs with Synthetic Data and Curriculum Learning
by: Upadhyay, Ojasw, et al.
Published: (2025)

ParallelSpec: Parallel Drafter for Efficient Speculative Decoding
by: Xiao, Zilin, et al.
Published: (2024)

Synth-Empathy: Towards High-Quality Synthetic Empathy Data
by: Liang, Hao, et al.
Published: (2024)

RL on Incorrect Synthetic Data Scales the Efficiency of LLM Math Reasoning by Eight-Fold
by: Setlur, Amrith, et al.
Published: (2024)

From 1,000,000 Users to Every User: Scaling Up Personalized Preference for User-level Alignment
by: Li, Jia-Nan, et al.
Published: (2025)

DRTriton: Large-Scale Synthetic Data Driven Reinforcement Learning for Triton Kernel Generation
by: Guo, Siqi, et al.
Published: (2026)

Enhancing Logical Reasoning in Large Language Models through Graph-based Synthetic Data
by: Zhou, Jiaming, et al.
Published: (2024)

FineInstructions: Scaling Synthetic Instructions to Pre-Training Scale
by: Patel, Ajay, et al.
Published: (2026)

MegaScale: Scaling Large Language Model Training to More Than 10,000 GPUs
by: Jiang, Ziheng, et al.
Published: (2024)

PersonaBOT: Bringing Customer Personas to Life with LLMs and RAG
by: Rizwan, Muhammed, et al.
Published: (2025)

Adaptive Querying with AI Persona Priors
by: Wang, Kaizheng, et al.
Published: (2026)

XKV: Personalized KV Cache Memory Reduction for Long-Context LLM Inference
by: Li, Weizhuo, et al.
Published: (2024)