3 papers
cs.CY2026
Hugging Carbon: Quantifying the Training Carbon Emissions of AI Models at Scale
Xinlei Wang, Ruibo Ming, Jing Qiu +2
The scaling-law era has transformed artificial intelligence (AI) from research into a global industry, but its rapid growth also raises concerns over energy usage, carbon emissions…
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,…
cs.AI2024
From News to Forecast: Integrating Event Analysis in LLM-Based Time Series Forecasting with Reflection
Xinlei Wang, Maike Feng, Jing Qiu +2
This paper introduces a novel approach that leverages Large Language Models (LLMs) and Generative Agents to enhance time series forecasting by reasoning across both text and time s…