3 papers
cs.AI2026
Controllable User Simulation
Guy Tennenholtz, Ofer Meshi, Amir Globerson +3
Using offline datasets to evaluate conversational agents often fails to cover rare scenarios or to support testing new policies. This has motivated the use of controllable user sim…
cs.IR2026
Efficient, Property-Aligned Fan-Out Retrieval via RL-Compiled Diffusion
Pengcheng Jiang, Judith Yue Li, Moonkyung Ryu +8
Many modern retrieval problems are set-valued: given a broad intent, the system must return a collection of results that optimizes higher-order properties (e.g., diversity, coverag…
cs.AI2025
Asking Clarifying Questions for Preference Elicitation With Large Language Models
Ali Montazeralghaem, Guy Tennenholtz, Craig Boutilier +1
Large Language Models (LLMs) have made it possible for recommendation systems to interact with users in open-ended conversational interfaces. In order to personalize LLM responses,…