2 papers
cs.IR2026
Improving LLM-based Recommendation with Self-Hard Negatives from Intermediate Layers
Bingqian Li, Bowen Zheng, Xiaolei Wang +5
Large language models (LLMs) have shown great promise in recommender systems, where supervised fine-tuning (SFT) is commonly used for adaptation. Subsequent studies further introdu…
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…