activity
20242026
most citedAILuminate: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons

4 citations · 8 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2026

TimeSage-EV: A Live Benchmark for Agentic Time Series Analysis in Evolving Environments

Qingren Yao, Yaxuan Kong, Yuqi Nie +6

Time series analysis in high-stakes domains relies on recurring data releases, where new observations can alter the evidence base and the validity of later conclusions. Existing ti…

cs.CL2026

TimeSage-MT: A Multi-Turn Benchmark for Evaluating Agentic Time Series Reasoning

Yaxuan Kong, Qingren Yao, Yuqi Nie +7

Time series data inform critical decisions across many real-world domains. While large language model (LLM) agents can analyze data through natural language and tools, it remains u…

cs.CY2025★ 4 cited

AILuminate: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons

Shaona Ghosh, Heather Frase, Adina Williams +99

The rapid advancement and deployment of AI systems have created an urgent need for standard safety-evaluation frameworks. This paper introduces AILuminate v1.0, the first comprehen…

cs.LG2024

Can time series forecasting be automated? A benchmark and analysis

Anvitha Thirthapura Sreedhara, Joaquin Vanschoren

In the field of machine learning and artificial intelligence, time series forecasting plays a pivotal role across various domains such as finance, healthcare, and weather. However,…

cs.IR2024★ 4 cited

A Standardized Machine-readable Dataset Documentation Format for Responsible AI

Nitisha Jain, Mubashara Akhtar, Joan Giner-Miguelez +15

Data is critical to advancing AI technologies, yet its quality and documentation remain significant challenges, leading to adverse downstream effects (e.g., potential biases) in AI…