3 papers
cs.IR2026
When History Misleads: Asymmetric Margin Supervision for Instruction-Guided LLM Generative Recommendation
Ming Yin, Yuhan Yang, Chen Chen +10
In instruction-guided generative recommendation, LLM-based recommenders need to balance two goals: responding to the user's current request and aligning with the preferences in the…
cs.AI2026
Simulate, Reason, Decide: Scientific Reasoning with LLMs for Simulation-Driven Decision Making
Yuhan Yang, Ruipu Li, Alexander Rodríguez
Scientific simulators are increasingly being integrated into LLM-driven systems for high-stakes simulation-driven decision-making. However, existing frameworks primarily use LLMs t…
cs.IR2026
Unleashing the Potential of Neighbors: Diffusion-based Latent Neighbor Generation for Session-based Recommendation
Yuhan Yang, Jie Zou, Guojia An +3
Session-based recommendation aims to predict the next item that anonymous users may be interested in, based on their current session interactions. Recent studies have demonstrated…