:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Xu, Longkun, Zhang, Xiaochun, Tuo, Qiantu, Li, Rui
Format:	Preprint
Published:	2026
Subjects:	Artificial Intelligence
Online Access:	https://arxiv.org/abs/2603.04873
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Self-Evolving Defect Detection Framework for Industrial Photovoltaic Systems
by: He, Haoyu, et al.
Published: (2026)

AME-TS: Anchored Mixture-of-Experts for Time Series Forecasting
by: Wang, Rui, et al.
Published: (2026)

SEA-Eval: A Benchmark for Evaluating Self-Evolving Agents Beyond Episodic Assessment
by: Jiang, Sihang, et al.
Published: (2026)

FLAIRR-TS -- Forecasting LLM-Agents with Iterative Refinement and Retrieval for Time Series
by: Jalori, Gunjan, et al.
Published: (2025)

A Lightweight, Transferable, and Self-Adaptive Framework for Intelligent DC Arc-Fault Detection in Photovoltaic Systems
by: Yang, Xiaoke, et al.
Published: (2026)

CODESKILL: Learning Self-Evolving Skills for Coding Agents
by: Li, Yanzhou, et al.
Published: (2026)

FlowTS: Time Series Generation via Rectified Flow
by: Hu, Yang, et al.
Published: (2024)

SciTS: Scientific Time Series Understanding and Generation with LLMs
by: Wu, Wen, et al.
Published: (2025)

ChatTS: Aligning Time Series with LLMs via Synthetic Data for Enhanced Understanding and Reasoning
by: Xie, Zhe, et al.
Published: (2024)

FiCoTS: Fine-to-Coarse LLM-Enhanced Hierarchical Cross-Modality Interaction for Time Series Forecasting
by: Lyu, Yafei, et al.
Published: (2025)

LeapTS: Rethinking Time Series Forecasting as Adaptive Multi-Horizon Scheduling
by: Pan, Sheng, et al.
Published: (2026)

TriTS: Time Series Forecasting from a Multimodal Perspective
by: Ao, Xiang
Published: (2026)

TS-RAG: Retrieval-Augmented Generation based Time Series Foundation Models are Stronger Zero-Shot Forecaster
by: Ning, Kanghui, et al.
Published: (2025)

Diffusion-TS: Interpretable Diffusion for General Time Series Generation
by: Yuan, Xinyu, et al.
Published: (2024)

DeepBooTS: Dual-Stream Residual Boosting for Drift-Resilient Time-Series Forecasting
by: Liang, Daojun, et al.
Published: (2025)

Baguan-TS: A Sequence-Native In-Context Learning Model for Time Series Forecasting with Covariates
by: Yang, Linxiao, et al.
Published: (2026)

TS-HTFA: Advancing Time Series Forecasting via Hierarchical Text-Free Alignment with Large Language Models
by: Wang, Pengfei, et al.
Published: (2024)

TS-LIF: A Temporal Segment Spiking Neuron Network for Time Series Forecasting
by: Feng, Shibo, et al.
Published: (2025)

Alita-G: Self-Evolving Generative Agent for Agent Generation
by: Qiu, Jiahao, et al.
Published: (2025)

APEX: Autonomous Policy Exploration for Self-Evolving LLM Agents
by: Li, Yibo, et al.
Published: (2026)

StaTS: Spectral Trajectory Schedule Learning for Adaptive Time Series Forecasting with Frequency Guided Denoiser
by: Zhang, Jintao, et al.
Published: (2026)

TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysis
by: Ye, Wen, et al.
Published: (2024)

AltTS: A Dual-Path Framework with Alternating Optimization for Multivariate Time Series Forecasting
by: Yuan, Zhihang, et al.
Published: (2026)

TS-Inverse: A Gradient Inversion Attack Tailored for Federated Time Series Forecasting Models
by: Meijer, Caspar, et al.
Published: (2025)

MambaTS: Improved Selective State Space Models for Long-term Time Series Forecasting
by: Cai, Xiuding, et al.
Published: (2024)

A Blueprint for Self-Evolving Coding Agents in Vehicle Aerodynamic Drag Prediction
by: Ren, Jinhui, et al.
Published: (2026)

TS-Agent: Understanding and Reasoning Over Raw Time Series via Iterative Insight Gathering
by: Liu, Penghang, et al.
Published: (2025)

Time Series Forecastability Measures
by: Wang, Rui, et al.
Published: (2025)

VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series Forecasters
by: Chen, Mouxiang, et al.
Published: (2024)

Bridging the Last Mile of Time Series Forecasting with LLM Agents
by: Liao, Yuhua, et al.
Published: (2026)

Autonomous Evolution of EDA Tools: Multi-Agent Self-Evolved ABC
by: Yu, Cunxi, et al.
Published: (2026)

EXG: Self-Evolving Agents with Experience Graphs
by: Jin, Yuxin, et al.
Published: (2026)

Self-Evolving Recommendation System: End-To-End Autonomous Model Optimization With LLM Agents
by: Wang, Haochen, et al.
Published: (2026)

Empowering Time Series Forecasting with LLM-Agents
by: Yeh, Chin-Chia Michael, et al.
Published: (2025)

DisMS-TS: Eliminating Redundant Multi-Scale Features for Time Series Classification
by: Liu, Zhipeng, et al.
Published: (2025)

Are Self-Attentions Effective for Time Series Forecasting?
by: Kim, Dongbin, et al.
Published: (2024)

SEDM: Scalable Self-Evolving Distributed Memory for Agents
by: Xu, Haoran, et al.
Published: (2025)

Evolving-RL: End-to-End Optimization of Experience-Driven Self-Evolving Capability within Agents
by: Fan, Zhiyuan, et al.
Published: (2026)

AgentDevel: Reframing Self-Evolving LLM Agents as Release Engineering
by: Zhang, Di
Published: (2026)

EvoConfig: Self-Evolving Multi-Agent Systems for Efficient Autonomous Environment Configuration
by: Guo, Xinshuai, et al.
Published: (2026)