3 citations · 5 across the 9 of their papers we have counts for
9 papers
Zeus: Towards Tuning-Free Foundation Model for Time Series Analysis
Yisong Fu, Zezhi Shao, Chengqing Yu +4
We present Zeus, a unified tuning-free Time Series Foundation Model (TSFM) that delivers superior performance across diverse analysis tasks without any task-specific fine-tuning. U…
KnowCoder-A1: Incentivizing Agentic Reasoning Capability with Outcome Supervision for KBQA
Zhuo Chen, Fei Wang, Zixuan Li +6
Knowledge Base Question Answering (KBQA) aims to answer natural-language questions over a structured Knowledge Base (KB). Recent work improves KBQA by adopting an agentic reasoning…
APT: Affine Prototype-Timestamp For Time Series Forecasting Under Distribution Shift
Yujie Li, Zezhi Shao, Chengqing Yu +4
Time series forecasting under distribution shift remains challenging, as existing deep learning models often rely on local statistical normalization (e.g., mean and variance) that…
Selective Learning for Deep Time Series Forecasting
Yisong Fu, Zezhi Shao, Chengqing Yu +5
Benefiting from high capacity for capturing complex temporal patterns, deep learning (DL) has significantly advanced time series forecasting (TSF). However, deep models tend to suf…
ARIES: Relation Assessment and Model Recommendation for Deep Time Series Forecasting
Fei Wang, Yujie Li, Zezhi Shao +5
Recent advancements in deep learning models for time series forecasting have been significant. These models often leverage fundamental time series properties such as seasonality an…
Merlin: Multi-View Representation Learning for Robust Multivariate Time Series Forecasting with Unfixed Missing Rates
Chengqing Yu, Fei Wang, Chuanguang Yang +6
Multivariate Time Series Forecasting (MTSF) involves predicting future values of multiple interrelated time series. Recently, deep learning-based MTSF models have gained significan…
BLAST: Balanced Sampling Time Series Corpus for Universal Forecasting Models
Zezhi Shao, Yujie Li, Fei Wang +7
The advent of universal time series forecasting models has revolutionized zero-shot forecasting across diverse domains, yet the critical role of data diversity in training these mo…
MPQ-DM: Mixed Precision Quantization for Extremely Low Bit Diffusion Models
Weilun Feng, Haotong Qin, Chuanguang Yang +7
Diffusion models have received wide attention in generation tasks. However, the expensive computation cost prevents the application of diffusion models in resource-constrained scen…
Context-Enhanced Multi-View Trajectory Representation Learning: Bridging the Gap through Self-Supervised Models
Tangwen Qian, Junhe Li, Yile Chen +4
Modeling trajectory data with generic-purpose dense representations has become a prevalent paradigm for various downstream applications, such as trajectory classification, travel t…