9 papers
Extending Myerson's Optimal Auctions to Correlated Bidders via Neural Network Interpolation
Mingyu Guo, Jiayuan Liu, Vincent Conitzer
We aim to design revenue-maximizing single-item auctions that are deterministic, strategy-proof, and ex post individually rational --- the quintessential fundamental model for opti…
Coopshift: Post-Training Amplifies The Memory Curse In LLM Cooperation
Jiayuan Liu, Shiyi Du, Tianqin Li +3
How does post-training change cooperation during repeated interaction? Within each of seven released model lineages, we compare pretrained (Base), supervised fine-tuned (SFT), and…
Truthful and Expected-Payment-Optimal Model Routing in Graph-Based Agentic Workflows
Jiayuan Liu, Mingyu Guo, Jiarui Gan +1
Assigning routine tasks to cheaper large language model (LLM) providers can reduce generation cost, but switching providers may require processing accumulated context again. Keepin…
LLM Advertisement based on Neuron Auctions
Peiran Yun, Wenxin Xu, Jiayuan Liu +4
As Large Language Models (LLMs) transition into conversational agents, generative advertising emerges as a crucial monetization strategy. However, embedding advertisements within u…
The Memory Curse: How Expanded Recall Erodes Cooperative Intent in LLM Agents
Jiayuan Liu, Tianqin Li, Shiyi Du +7
Context window expansion is often treated as a straightforward capability upgrade for LLMs, but we find it systematically fails in multi-agent social dilemmas. Across 7 LLMs and 4…
Why Search When You Can Transfer? Amortized Agentic Workflow Design from Structural Priors
Shiyi Du, Jiayuan Liu, Weihua Du +6
Automated agentic workflow design currently relies on per-task iterative search, which is computationally prohibitive and fails to reuse structural knowledge across tasks. We obser…
The Consensus Trap: Rescuing Multi-Agent LLMs from Adversarial Majorities via Token-Level Collaboration
Jiayuan Liu, Shiyi Du, Weihua Du +2
Multi-agent large language model (LLM) architectures increasingly rely on response-level aggregation, such as Majority Voting (MAJ), to raise reasoning ceilings. However, in open e…
Incentive-Aware Multi-Fidelity Optimization for Generative Advertising in Large Language Models
Jiayuan Liu, Barry Wang, Jiarui Gan +4
Generative advertising in large language model (LLM) responses requires optimizing sponsorship configurations under two strict constraints: the strategic behavior of advertisers an…
How Many Votes is a Lie Worth? Measuring Strategyproofness through Resource Augmentation
Ratip Emin Berker, Vincent Conitzer, Eden Hartman +2
It is well known, by the Gibbard-Satterthwaite Theorem, that when there are more than two candidates, any non-dictatorial voting rule can be manipulated by untruthful voters. But h…