3 papers
cs.LG2026
Separating personal from population gains when calibrating EEG foundation models for new users
Xilin Tao, Kani Chen
Foundation models are increasingly adapted to individual users, but an apparent personalization gain can simply reflect a stronger population model. This distinction matters for br…
cs.CL2026
FinBoardBench: Benchmarking Dynamic Wealth Management and Strategic Financial Reasoning of LLMs via Board Game Simulations
Xuesi Hu, Peng Wang, Jinpeng Miao +7
Recently, large language models (LLMs) have achieved superior performance in static financial reasoning and simple dynamic trading tasks. However, existing static financial benchma…
cs.CL2026
Can Large Language Models Resolve Semantic Discrepancy in Self-Destructive Subcultures? Evidence from Jirai Kei
Peng Wang, Xilin Tao, Siyi Yao +5
Self-destructive behaviors are linked to complex psychological states and can be challenging to diagnose. These behaviors may be even harder to identify within subcultural groups d…