collaborators

5 papers

cs.AI2026

EarthVerse: Benchmarking Scientific Agents Across Dynamic Earth Systems and Natural Hazards

Zhiqing Cui, Xinxiang Yin, Yihong Tang +11

Earth-system analysis reconstructs changing physical processes from observations that differ in source, scale, timing, and modality. Natural hazards make this work consequential be…

cs.LG2026

Breaking the Regional Barrier: Inductive Semantic Topology Learning for Worldwide Air Quality Forecasting

Zhiqing Cui, Siru Zhong, Ming Jin +3

Global air quality forecasting grapples with extreme spatial heterogeneity and the poor generalization of existing transductive models to unseen regions. To tackle this, we propose…

cs.AI2026

Rationale-Grounded In-Context Learning for Time Series Reasoning with Multimodal Large Language Models

Qingxiang Liu, Zhiqing Cui, Xiaoliang Luo +7

The underperformance of existing multimodal large language models for time series reasoning lies in the absence of rationale priors that connect temporal observations to their down…

cs.AI2026

DropoutTS: Sample-Adaptive Dropout for Robust Time Series Forecasting

Siru Zhong, Yiqiu Liu, Zhiqing Cui +4

Deep time series models are vulnerable to noisy data ubiquitous in real-world applications. Existing robustness strategies either prune data or rely on costly prior quantification,…

cs.AI2025

Augur: Modeling Covariate Causal Associations in Time Series via Large Language Models

Zhiqing Cui, Binwu Wang, Qingxiang Liu +4

Large language models (LLM) have emerged as a promising avenue for time series forecasting, offering the potential to integrate multimodal data. However, existing LLM-based approac…