Rating Quality of Diverse Time Series Data by Meta-learning from LLM Judgment

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wu, Shunyu, Li, Dan, Feng, Wenjie, Ye, Haozheng, Lou, Jian, Ng, See-Kiong
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Integrating Time Series into LLMs via Multi-layer Steerable Embedding Fusion for Enhanced Forecasting
by: Chen, Zhuomin, et al.
Published: (2025)

Lightweight Time Series Data Valuation on Time Series Foundation Models via In-Context Finetuning
by: Wu, Shunyu, et al.
Published: (2025)

WaveMoE: A Wavelet-Enhanced Mixture-of-Experts Foundation Model for Time Series Forecasting
by: Wu, Shunyu, et al.
Published: (2026)

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision
by: Zhou, Jiahui, et al.
Published: (2025)

Time Series Reasoning via Process-Verifiable Thinking Data Synthesis and Scheduling for Tailored LLM Reasoning
by: Zhou, Jiahui, et al.
Published: (2026)

BACE-RUL: A Bi-directional Adversarial Network with Covariate Encoding for Machine Remaining Useful Life Prediction
by: Zhang, Zekai, et al.
Published: (2025)

Beyond Prompt-Induced Lies: Investigating LLM Deception on Benign Prompts
by: Wu, Zhaomin, et al.
Published: (2025)

Empowering VLMs for Few-Shot Multimodal Time Series Classification via Tailored Agentic Reasoning
by: Li, Lin, et al.
Published: (2026)

Test-Time Scaling in Reasoning Models Is Not Effective for Knowledge-Intensive Tasks Yet
by: Zhao, James Xu, et al.
Published: (2025)

FD-LLM: Large Language Model for Fault Diagnosis of Machines
by: Qaid, Hamzah A. A. M., et al.
Published: (2024)

Multi-Modal One-Shot Federated Ensemble Learning for Medical Data with Vision Large Language Model
by: Wang, Naibo, et al.
Published: (2025)

Meta-learning to Address Data Shift in Time Series Classification
by: Myren, Samuel, et al.
Published: (2026)

GLOW: Graph-Language Co-Reasoning for Agentic Workflow Performance Prediction
by: Guan, Wei, et al.
Published: (2025)

Collaborative Imputation of Urban Time Series through Cross-city Meta-learning
by: Nie, Tong, et al.
Published: (2025)

Source Attribution for Large Language Model-Generated Data
by: Wang, Jingtan, et al.
Published: (2023)

Ferret: Federated Full-Parameter Tuning at Scale for Large Language Models
by: Shu, Yao, et al.
Published: (2024)

How Does Response Length Affect Long-Form Factuality
by: Zhao, James Xu, et al.
Published: (2025)

Dipper: Diversity in Prompts for Producing Large Language Model Ensembles in Reasoning tasks
by: Lau, Gregory Kang Ruey, et al.
Published: (2024)

Synthetic Series-Symbol Data Generation for Time Series Foundation Models
by: Wang, Wenxuan, et al.
Published: (2025)

ActiveDPO: Active Direct Preference Optimization for Sample-Efficient Alignment
by: Lin, Xiaoqiang, et al.
Published: (2025)

On Newton's Method to Unlearn Neural Networks
by: Bui, Nhung, et al.
Published: (2024)

Prompt Optimization with Human Feedback
by: Lin, Xiaoqiang, et al.
Published: (2024)

Mitigating Data Scarcity in Time Series Analysis: A Foundation Model with Series-Symbol Data Generation
by: Wang, Wenxuan, et al.
Published: (2025)

Internalizing Curriculum Judgment for LLM Reinforcement Fine-Tuning
by: Zheng, Han, et al.
Published: (2026)

Temporal Gaussian Copula For Clinical Multivariate Time Series Data Imputation
by: Su, Ye, et al.
Published: (2025)

When LLM Meets Time Series: Can LLMs Perform Multi-Step Time Series Reasoning and Inference
by: Ye, Wen, et al.
Published: (2025)

A Multi-scenario Attention-based Generative Model for Personalized Blood Pressure Time Series Forecasting
by: Wan, Cheng, et al.
Published: (2024)

Geneshift: Impact of different scenario shift on Jailbreaking LLM
by: Wu, Tianyi, et al.
Published: (2025)

GLA-DA: Global-Local Alignment Domain Adaptation for Multivariate Time Series
by: Tu, Gang, et al.
Published: (2024)

STEER: Inference-Time Risk Control via Constrained Quality-Diversity Search
by: Yang, Eric, et al.
Published: (2026)

STAR: Semantic-Tuned and Tail-Adaptive Retriever for Graph-Augmented Generation
by: Li, Shuai, et al.
Published: (2026)

Prompt Optimization with EASE? Efficient Ordering-aware Automated Selection of Exemplars
by: Wu, Zhaoxuan, et al.
Published: (2024)

Use Your INSTINCT: INSTruction optimization for LLMs usIng Neural bandits Coupled with Transformers
by: Lin, Xiaoqiang, et al.
Published: (2023)

Rethinking Machine Unlearning in Image Generation Models
by: Liu, Renyang, et al.
Published: (2025)

From Time Series Analysis to Question Answering: A Survey in the LLM Era
by: Li, Wei, et al.
Published: (2025)

Tri-Level Navigator: LLM-Empowered Tri-Level Learning for Time Series OOD Generalization
by: Jian, Chengtao, et al.
Published: (2024)

RandomNet: Clustering Time Series Using Untrained Deep Neural Networks
by: Li, Xiaosheng, et al.
Published: (2024)

PIED: Physics-Informed Experimental Design for Inverse Problems
by: Hemachandra, Apivich, et al.
Published: (2025)

PINNACLE: PINN Adaptive ColLocation and Experimental points selection
by: Lau, Gregory Kang Ruey, et al.
Published: (2024)

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models
by: Wen, Songkang, et al.
Published: (2024)