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Peiyuan Liu

16 papers hereh-index 10569 citations20 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author13

Across the 16 of 16 papers where every author was matched, so the position is known.

fields
  • cs.LG12
  • cs.CE3
  • cs.AI1
same name
  • Peiyuan Liu — 3 papers, h 2
  • Peiyuan Liu — 3 papers, h 6
  • Peiyuan Liu — 1 paper, h 15
  • Peiyuan Liu — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232026
most citedCALF: Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning

5 citations · 13 across the 16 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.LG2024★ 4 cited

TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting

Peiyuan Liu, Beiliang Wu, Yifan Hu +4

Non-stationarity poses significant challenges for multivariate time series forecasting due to the inherent short-term fluctuations and long-term trends that can lead to spurious re…

cs.CE2024

Generative Pre-Trained Diffusion Paradigm for Zero-Shot Time Series Forecasting

Jiarui Yang, Tao Dai, Naiqi Li +6

In recent years, generative pre-trained paradigms such as Large Language Models (LLMs) and Large Vision Models (LVMs) have achieved revolutionary advancements and widespread real-w…

cs.LG2024★ 2 cited

Adaptive Multi-Scale Decomposition Framework for Time Series Forecasting

Yifan Hu, Peiyuan Liu, Peng Zhu +2

Transformer-based and MLP-based methods have emerged as leading approaches in time series forecasting (TSF). While Transformer-based methods excel in capturing long-range dependenc…

cs.LG2024★ 5 cited

CALF: Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning

Peiyuan Liu, Hang Guo, Tao Dai +5

Deep learning (e.g., Transformer) has been widely and successfully used in multivariate time series forecasting (MTSF). Unlike existing methods that focus on training models from a…

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