:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Wang, Haohui, Qi, Jingyuan, Chen, Jianpeng, Wu, Jun, Huang, Lifu, Zheng, Lecheng, Choi, Kevin, Veeramani, Balaji, Bowen, Edward, Hu, Alison, Cody, Tyler, Zhou, Dawei
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2511.13640
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

EvoluNet: Advancing Dynamic Non-IID Transfer Learning on Graphs
by: Wang, Haohui, et al.
Published: (2023)

LENSLLM: Unveiling Fine-Tuning Dynamics for LLM Selection
by: Zeng, Xinyue, et al.
Published: (2025)

MetamatBench: Integrating Heterogeneous Data, Computational Tools, and Visual Interface for Metamaterial Discovery
by: Chen, Jianpeng, et al.
Published: (2025)

Towards Heterogeneous Long-tailed Learning: Benchmarking, Metrics, and Toolbox
by: Wang, Haohui, et al.
Published: (2023)

Scaling Laws for Mixture Pretraining Under Data Constraints
by: Sedova, Anastasiia, et al.
Published: (2026)

Indiaʼs Integration Into Global Value Chains: Policy Approaches to Growth and Industrial Upgrading
by: Veeramani Choorikkadan
Published: (2026)

A Framework for Assessing the Value of RFID Implementation by Tier-One Suppliers to Major Retailers
by: Dharmaraj Veeramani
Published: (2008)

Principled Synthetic Data Enables the First Scaling Laws for LLMs in Recommendation
by: Zhang, Benyu, et al.
Published: (2026)

Beyond Real Data: Synthetic Data through the Lens of Regularization
by: Shidani, Amitis, et al.
Published: (2025)

Scaling Tumor Segmentation: Best Lessons from Real and Synthetic Data
by: Chen, Qi, et al.
Published: (2025)

Scaling Laws for Optimal Data Mixtures
by: Shukor, Mustafa, et al.
Published: (2025)

Balancing Learning Rates Across Layers: Exact Two-Step Dynamics and Optimal Scaling in Linear Neural Networks
by: Pang, Tianyu, et al.
Published: (2026)

A Large-Scale Real-World Evaluation of LLM-Based Virtual Teaching Assistant
by: Kweon, Sunjun, et al.
Published: (2025)

MoNDE: Mixture of Near-Data Experts for Large-Scale Sparse Models
by: Kim, Taehyun, et al.
Published: (2024)

DKT2: Revisiting Applicable and Comprehensive Knowledge Tracing in Large-Scale Data
by: Zhou, Yiyun, et al.
Published: (2025)

Addressing Bias in Spoken Language Systems Used in the Development and Implementation of Automated Child Language‐Based Assessment
by: Alison L. Bailey, et al.
Published: (2025)

Realistic Synthetic Household Data Generation at Scale
by: Singh, Siddharth, et al.
Published: (2026)

Scaling Laws of Synthetic Data for Language Models
by: Qin, Zeyu, et al.
Published: (2025)

Scaling Up Forest Vision with Synthetic Data
by: She, Yihang, et al.
Published: (2025)

Patient-Zero: Scaling Synthetic Patient Agents to Real-World Distributions without Real Patient Data
by: Lai, Yunghwei, et al.
Published: (2025)

Citations and Trust in LLM Generated Responses
by: Ding, Yifan, et al.
Published: (2025)

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

Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training
by: Ruan, Hongzhi, et al.
Published: (2026)

Scaling Text-Rich Image Understanding via Code-Guided Synthetic Multimodal Data Generation
by: Yang, Yue, et al.
Published: (2025)

Scaling Trends for Data Poisoning in LLMs
by: Bowen, Dillon, et al.
Published: (2024)

Improving Intrusion Detection with Domain-Invariant Representation Learning in Latent Space
by: Roy, Padmaksha, et al.
Published: (2023)

Improving the Scaling Laws of Synthetic Data with Deliberate Practice
by: Askari-Hemmat, Reyhane, et al.
Published: (2025)

Synthetica: Large Scale Synthetic Data for Robot Perception
by: Singh, Ritvik, et al.
Published: (2024)

Characterizing Model Behavior Under Synthetic Data Training: An Empirical Study Across Scales and Mixing Ratios
by: Du, Y., et al.
Published: (2025)

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

MetaScientist: A Human-AI Synergistic Framework for Automated Mechanical Metamaterial Design
by: Qi, Jingyuan, et al.
Published: (2024)

Bringing Textual Prompt to AI-Generated Image Quality Assessment
by: Qu, Bowen, et al.
Published: (2024)

SynPlay: Large-Scale Synthetic Human Data with Real-World Diversity for Aerial-View Perception
by: Yim, Jinsub, et al.
Published: (2024)

Understanding LLM Behaviors via Compression: Data Generation, Knowledge Acquisition and Scaling Laws
by: Pan, Zhixuan, et al.
Published: (2025)

Large-Scale Multiple Testing of Composite Null Hypotheses Under Heteroskedasticity
by: Gang, Bowen, et al.
Published: (2023)

DALDA: Data Augmentation Leveraging Diffusion Model and LLM with Adaptive Guidance Scaling
by: Jung, Kyuheon, et al.
Published: (2024)

Multilingual Multi-Label Emotion Classification at Scale with Synthetic Data
by: Borisov, Vadim
Published: (2026)

Scaling Speech-Text Pre-training with Synthetic Interleaved Data
by: Zeng, Aohan, et al.
Published: (2024)

Scaling Planning for Automated Driving using Simplistic Synthetic Data
by: Stoll, Martin, et al.
Published: (2023)

Demystifying Synthetic Data in LLM Pre-training: A Systematic Study of Scaling Laws, Benefits, and Pitfalls
by: Kang, Feiyang, et al.
Published: (2025)