2 papers
q-fin.GN2025
The Memorization Problem: Can We Trust LLMs' Economic Forecasts?
Alejandro Lopez-Lira, Yuehua Tang, Mingyin Zhu
Large language models (LLMs) cannot be trusted for economic forecasts during periods covered by their training data. Counterfactual forecasting ability is non-identified when the m…
cs.AI2025
FullStack Bench: Evaluating LLMs as Full Stack Coders
Bytedance-Seed-Foundation-Code-Team, :, Yao Cheng +53
As the capabilities of code large language models (LLMs) continue to expand, their applications across diverse code intelligence domains are rapidly increasing. However, most exist…