ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2402.02713
  4. Cited By
Position: What Can Large Language Models Tell Us about Time Series
  Analysis
v1v2 (latest)

Position: What Can Large Language Models Tell Us about Time Series Analysis

5 February 2024
Ming Jin
Yifan Zhang
Wei Chen
Kexin Zhang
Yuxuan Liang
Bin Yang
James Evans
Shirui Pan
Qingsong Wen
    AI4TS
ArXiv (abs)PDFHTMLGithub

Papers citing "Position: What Can Large Language Models Tell Us about Time Series Analysis"

18 / 18 papers shown
QuAnTS: Question Answering on Time Series
QuAnTS: Question Answering on Time Series
Felix Divo
Maurice Kraus
Anh Q. Nguyen
Hao Xue
Imran Razzak
Flora D. Salim
Kristian Kersting
Devendra Singh Dhami
140
1
0
07 Nov 2025
TsLLM: Augmenting LLMs for General Time Series Understanding and Prediction
TsLLM: Augmenting LLMs for General Time Series Understanding and Prediction
Felix Parker
Nimeesha Chan
Chi Zhang
Kimia Ghobadi
AI4TS
175
2
0
01 Oct 2025
A Survey of Reasoning and Agentic Systems in Time Series with Large Language Models
A Survey of Reasoning and Agentic Systems in Time Series with Large Language Models
Ching Chang
Yidan Shi
Defu Cao
Wei Yang
Jeehyun Hwang
...
Jiacheng Pang
Wei-Yao Wang
Yan Liu
Wen-Chih Peng
Tien-Fu Chen
AI4TSLRM
254
11
0
15 Sep 2025
CC-Time: Cross-Model and Cross-Modality Time Series Forecasting
CC-Time: Cross-Model and Cross-Modality Time Series Forecasting
Peng Chen
Yihang Wang
Yang Shu
Yunyao Cheng
Kai Zhao
Zhongwen Rao
Lujia Pan
Bin Yang
Chenjuan Guo
AI4TSVLM
220
3
0
17 Aug 2025
RAST: A Retrieval Augmented Spatio-Temporal Framework for Traffic Prediction
RAST: A Retrieval Augmented Spatio-Temporal Framework for Traffic Prediction
Weilin Ruan
Xilin Dang
Ziyu Zhou
Sisuo Lyu
Yuxuan Liang
AI4TS
471
1
0
14 Aug 2025
Prioritizing Alignment Paradigms over Task-Specific Model Customization in Time-Series LLMs
Prioritizing Alignment Paradigms over Task-Specific Model Customization in Time-Series LLMs
Wei Li
Yunyao Cheng
Xinli Hao
Chaohong Ma
Yuxuan Liang
Bin Yang
Christian S.Jensen
Xiaofeng Meng
AI4TS
199
0
0
13 Jun 2025
Time Series Forecasting as Reasoning: A Slow-Thinking Approach with Reinforced LLMs
Time Series Forecasting as Reasoning: A Slow-Thinking Approach with Reinforced LLMs
Yucong Luo
Yitong Zhou
Mingyue Cheng
Jiahao Wang
Daoyu Wang
Tingyue Pan
Jintao Zhang
AI4TSLRM
355
21
0
12 Jun 2025
Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision
Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision
Jiahui Zhou
Dan Li
Lin Li
Zhuomin Chen
Shunyu Wu
Haozheng Ye
Jian Lou
Costas J. Spanos
AI4TSLRM
250
5
0
01 Jun 2025
Large Language models for Time Series Analysis: Techniques, Applications, and Challenges
Large Language models for Time Series Analysis: Techniques, Applications, and Challenges
Feifei Shi
Xueyan Yin
Kang Wang
Wanyu Tu
Qifu Sun
Huansheng Ning
AI4TS
231
1
0
21 May 2025
Boost Post-Training Quantization via Null Space Optimization for Large Language Models
Boost Post-Training Quantization via Null Space Optimization for Large Language Models
Jiaqi Zhao
Miao Zhang
Deng Xiang
Liqiang Nie
Weili Guan
L. Nie
MQ
265
0
0
21 May 2025
How Effective are Large Time Series Models in Hydrology? A Study on Water Level Forecasting in Everglades
How Effective are Large Time Series Models in Hydrology? A Study on Water Level Forecasting in Everglades
Rahuul Rangaraj
Jimeng Shi
Azam Shirali
Rajendra Paudel
Yanzhao Wu
Giri Narasimhan
372
3
0
02 May 2025
Enhancing Time Series Forecasting via Multi-Level Text Alignment with LLMs
Enhancing Time Series Forecasting via Multi-Level Text Alignment with LLMs
Taibiao Zhao
Xiaobing Chen
Mingxuan Sun
AI4TS
401
7
0
10 Apr 2025
Can LLMs Understand Time Series Anomalies?
Can LLMs Understand Time Series Anomalies?International Conference on Learning Representations (ICLR), 2024
Zihao Zhou
Rose Yu
AI4TS
448
40
0
13 Mar 2025
Vision-Enhanced Time Series Forecasting via Latent Diffusion Models
Vision-Enhanced Time Series Forecasting via Latent Diffusion Models
Weilin Ruan
Siru Zhong
Haomin Wen
Yuxuan Liang
AI4TS
416
9
0
16 Feb 2025
Transfer Learning with Foundational Models for Time Series Forecasting using Low-Rank Adaptations
Transfer Learning with Foundational Models for Time Series Forecasting using Low-Rank AdaptationsInformation Fusion (Inf. Fusion), 2024
M. Germán-Morales
A. J. Rivera-Rivas
M. J. del Jesus Díaz
C. J. Carmona
AI4TSAI4CE
793
10
0
15 Oct 2024
TSFM-Bench: A Comprehensive and Unified Benchmarking of Foundation Models for Time Series Forecasting
TSFM-Bench: A Comprehensive and Unified Benchmarking of Foundation Models for Time Series Forecasting
Zhe Li
Xiangfei Qiu
Peng Chen
Yihang Wang
Hanyin Cheng
...
Jiaxi Hu
Chenjuan Guo
Aoying Zhou
Qingsong Wen
Christian S. Jensen
AI4TS
552
8
0
15 Oct 2024
Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts
Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of ExpertsInternational Conference on Learning Representations (ICLR), 2024
Xiaoming Shi
Shiyu Wang
Yuqi Nie
Dianqi Li
Zhou Ye
Qingsong Wen
Ming Jin
AI4TS
768
232
0
24 Sep 2024
Unleashing The Power of Pre-Trained Language Models for Irregularly Sampled Time Series
Unleashing The Power of Pre-Trained Language Models for Irregularly Sampled Time Series
Weijia Zhang
Chenlong Yin
Hao Liu
Hui Xiong
AI4TS
420
3
0
12 Aug 2024
1
Page 1 of 1