The paper presents TimeSeriesGym, a benchmark of 34 time series ML engineering challenges for AI agents, and shows that current agents produce valid solutions in 57.3% of tasks but reasonable ones in only 12.5%.
Aqua: A benchmarking tool for label quality assessment
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents
The paper presents TimeSeriesGym, a benchmark of 34 time series ML engineering challenges for AI agents, and shows that current agents produce valid solutions in 57.3% of tasks but reasonable ones in only 12.5%.