3 papers
cs.CL2026
Entropy-Gated Branching for Efficient Test-Time Reasoning
Xianzhi Li, Ethan Callanan, Abdellah Ghassel +1
Test-time compute methods can significantly improve the reasoning capabilities and problem-solving accuracy of large language models (LLMs). However, these approaches require subst…
q-fin.PM2025
Learning to Manage Investment Portfolios beyond Simple Utility Functions
Maarten P. Scholl, Mahmoud Mahfouz, Anisoara Calinescu +1
While investment funds publicly disclose their objectives in broad terms, their managers optimize for complex combinations of competing goals that go beyond simple risk-return trad…
cs.CL2025
InvestAlign: Overcoming Data Scarcity in Aligning Large Language Models with Investor Decision-Making Processes under Herd Behavior
Huisheng Wang, Zhuoshi Pan, Hangjing Zhang +3
Aligning Large Language Models (LLMs) with investor decision-making processes under herd behavior is a critical challenge in behavioral finance, which grapples with a fundamental l…