3 papers
cs.AI2026
Inferring Events from Time Series using Language Models
Mingtian Tan, Mike A. Merrill, Zack Gottesman +3
A common goal in analyzing time series data is to understand how events cause observed variations. We study whether Large Language Models (LLMs) can infer natural language events a…
cs.LG2026
LEAF: A Living Benchmark for Event-Augmented Forecasting
Mingtian Tan, Mihir Parmar, Palash Goyal +5
Large Language Models (LLMs) are increasingly applied to forecasting. To evaluate this capability while mitigating pre-training data contamination, several living benchmarks have b…
cs.AI2025
Toward Reasoning-Centric Time-Series Analysis
Xinlei Wang, Mingtian Tan, Jing Qiu +2
Traditional time series analysis has long relied on pattern recognition, trained on static and well-established benchmarks. However, in real-world settings -- where policies shift,…