activity
20192026
most citedgCastle: A Python Toolbox for Causal Discovery

27 citations · 49 across the 19 of their papers we have counts for

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Showing 2026Show all

7 papers · 1 filter

cs.LG2026

Instance-Adaptive Prompts as Context for Time-Series Foundation Models

Zehao Xiao, Shifeng Xie, Lei Zan +5

Longer histories can improve time-series foundation models (TSFMs), but require substantially higher inference cost. We therefore ask whether contextual information can be provided…

cs.LG2026

Tabby: An Open Pretraining Recipe for Time Series Foundation Models

Shifeng Xie, Bahaeddine Abdessalem, Zehao Xiao +9

In this report, we release Tabby, a long context probabilistic time series foundation model, together with a complete and open recipe of how it was built. Tabby adopts an encoder-o…

cs.LG2026

FlowTSFM: Turning Encoder Depth into Quantile Transport

Bahaeddine Abdessalem, Shifeng Xie, Zehao Xiao +6

Encoder-based time series foundation models (TSFMs) typically rely on deep stacks of independently parameterized Transformer layers, where only the final forecast is supervised and…

cs.LG2026

ChorusTIC: Training-Free Multivariate Time Series Classification via Chorus In-Context Learning

Juntao Fang, Shifeng Xie, Ruichu Cai +6

Time series classification underpins applications in healthcare, sensing, and industrial monitoring. Although time series foundation models support forecasting and transferable rep…

cs.LG2026

Post-Training in Time Series Foundation Models: A Unifying Framework

Shifeng Xie, Ambroise Odonnat, Zehao Xiao +7

Time series foundation models (TSFMs) have emerged as general-purpose models for time series analysis, but pretraining alone is often insufficient for reliable downstream deploymen…

cs.CL2026

SERE: Structural Example Retrieval for Enhancing LLMs in Event Causality Identification

Zhifeng Hao, Zhongjie Chen, Junhao Lu +5

Event Causality Identification (ECI) requires models to determine whether a given pair of events in a context exhibits a causal relationship. While Large Language Models (LLMs) hav…

cs.LG2026

Rethinking Zero-Shot Time Series Classification: From Task-specific Classifiers to In-Context Inference

Juntao Fang, Shifeng Xie, Shengbin Nie +7

The zero-shot evaluation of time series foundation models (TSFMs) for classification typically uses a frozen encoder followed by a task-specific classifier. However, this practice…