2 papers
cs.LG2026
TuneAhead: Predicting Fine-tuning Performance Before Full Training Begins
Yuxiang Luo, Haonan Long, Chen Wang +6
Fine-tuning large language models (LLMs) is compute-intensive and error-prone: model performance depends sensitively on data quality and hyperparameter choices, and naïve runs can…
cs.CE2025
Time Travel is Cheating: Going Live with DeepFund for Real-Time Fund Investment Benchmarking
Changlun Li, Yao Shi, Chen Wang +7
Large Language Models (LLMs) have demonstrated notable capabilities across financial tasks, including financial report summarization, earnings call transcript analysis, and asset c…