8 papers
Common-agency Games for Multi-Objective Test-Time Alignment
Baiting Chen, Tong Zhu, Rui Yu +1
Aligning large language models (LLMs) with human preferences is inherently multi-objective: different users and evaluation criteria impose heterogeneous and often conflicting requi…
Mechanism Design for Quality-Preserving LLM Advertising
Jiale Han, Xiaowu Dai
Embedding advertisements into large language model (LLM) outputs introduces a fundamental tension: revenue optimization can distort content and degrade user experience. Existing ap…
Prompt-Dependent Ranking of Large Language Models with Uncertainty Quantification
Angel Rodrigo Avelar Menendez, Yufeng Liu, Xiaowu Dai
Rankings derived from pairwise comparisons are central to many economic and computational systems. In the context of large language models (LLMs), rankings are typically constructe…
Auto-bidding under Return-on-Spend Constraints with Uncertainty Quantification
Jiale Han, Chun Gan, Chengcheng Zhang +4
Auto-bidding systems are widely used in advertising to automatically determine bid values under constraints such as total budget and Return-on-Spend (RoS) targets. Existing works o…
Variance Reduction via Resampling and Experience Replay
Jiale Han, Xiaowu Dai, Yuhua Zhu
Experience replay is a foundational technique in reinforcement learning that enhances learning stability by storing past experiences in a replay buffer and reusing them during trai…
Incentivizing Truthful Language Models via Peer Elicitation Games
Baiting Chen, Tong Zhu, Jiale Han +3
Large Language Models (LLMs) have demonstrated strong generative capabilities but remain prone to inconsistencies and hallucinations. We introduce Peer Elicitation Games (PEG), a t…