1 citations · 1 across the 11 of their papers we have counts for
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Learning in Stackelberg Mean Field Games: A Non-Asymptotic Analysis
Sihan Zeng, Benjamin Patrick Evans, Sujay Bhatt +3
We study policy optimization in Stackelberg mean field games (MFGs), a hierarchical framework for modeling the strategic interaction between a single leader and an infinitely large…
QueryBandits for Hallucination Mitigation: Exploiting Semantic Features for No-Regret Rewriting
Nicole Cho, William Watson, Alec Koppel +2
Advanced reasoning capabilities in Large Language Models (LLMs) have caused higher hallucination prevalence; yet most mitigation work focuses on after-the-fact filtering rather tha…
Collab: Controlled Decoding using Mixture of Agents for LLM Alignment
Souradip Chakraborty, Sujay Bhatt, Udari Madhushani Sehwag +7
Alignment of Large Language models (LLMs) is crucial for safe and trustworthy deployment in applications. Reinforcement learning from human feedback (RLHF) has emerged as an effect…
Efficient Inverse Multiagent Learning
Denizalp Goktas, Amy Greenwald, Sadie Zhao +2
In this paper, we study inverse game theory (resp. inverse multiagent learning) in which the goal is to find parameters of a game's payoff functions for which the expected (resp. s…
Decentralized Convergence to Equilibrium Prices in Trading Networks
Edwin Lock, Benjamin Patrick Evans, Eleonora Kreacic +4
We propose a decentralized market model in which agents can negotiate bilateral contracts. This builds on a similar, but centralized, model of trading networks introduced by Hatfie…
Regularized Proportional Fairness Mechanism for Resource Allocation Without Money
Sihan Zeng, Sujay Bhatt, Alec Koppel +1
Mechanism design in resource allocation studies dividing limited resources among self-interested agents whose satisfaction with the allocation depends on privately held utilities.…