1 citations · 3 across the 12 of their papers we have counts for
13 papers
Can Watermarking Techniques Help Prevent LLM Model Stealing?
Elette Boyle, MohammadTaghi Hajiaghayi, Keivan Rezaei +2
Model stealing attacks have recently been introduced, enabling the extraction of precise information from black-box commercial language models. In this work, we propose defense met…
Fairness and Efficiency in Online Class Matching
MohammadTaghi Hajiaghayi, Shayan Chashm Jahan, Mohammad Sharifi +2
The online bipartite matching problem, extensively studied in the literature, deals with the allocation of online arriving vertices (items) to a predetermined set of offline vertic…
Gains-from-Trade in Bilateral Trade with a Broker
Ilya Hajiaghayi, MohammadTaghi Hajiaghayi, Gary Peng +1
We study bilateral trade with a broker, where a buyer and seller interact exclusively through the broker. The broker strategically maximizes her payoff through arbitrage by trading…
Ad Auctions for LLMs via Retrieval Augmented Generation
MohammadTaghi Hajiaghayi, Sébastien Lahaie, Keivan Rezaei +1
In the field of computational advertising, the integration of ads into the outputs of large language models (LLMs) presents an opportunity to support these services without comprom…
Dueling Over Dessert, Mastering the Art of Repeated Cake Cutting
Simina Brânzei, MohammadTaghi Hajiaghayi, Reed Phillips +2
We consider the setting of repeated fair division between two players, denoted Alice and Bob, with private valuations over a cake. In each round, a new cake arrives, which is ident…
Replication-proof Bandit Mechanism Design with Bayesian Agents
Suho Shin, Seyed A. Esmaeili, MohammadTaghi Hajiaghayi
We study the problem of designing replication-proof bandit mechanisms when agents strategically register or replicate their own arms to maximize their payoff. Specifically, we cons…
An Improved Relaxation for Oracle-Efficient Adversarial Contextual Bandits
Kiarash Banihashem, MohammadTaghi Hajiaghayi, Suho Shin +1
We present an oracle-efficient relaxation for the adversarial contextual bandits problem, where the contexts are sequentially drawn i.i.d from a known distribution and the cost seq…
Online Advertisements with LLMs: Opportunities and Challenges
Soheil Feizi, MohammadTaghi Hajiaghayi, Keivan Rezaei +1
This paper explores the potential for leveraging Large Language Models (LLM) in the realm of online advertising systems. We introduce a general framework for LLM advertisement, con…
Regret Analysis of Repeated Delegated Choice
MohammadTaghi Hajiaghayi, Mohammad Mahdavi, Keivan Rezaei +1
We present a study on a repeated delegated choice problem, which is the first to consider an online learning variant of Kleinberg and Kleinberg, EC'18. In this model, a principal i…
Delegating to Multiple Agents
MohammadTaghi Hajiaghayi, Keivan Rezaei, Suho Shin
We consider a multi-agent delegation mechanism without money. In our model, given a set of agents, each agent has a fixed number of solutions which is exogenous to the mechanism, a…
Bandit Social Learning: Exploration under Myopic Behavior
Kiarash Banihashem, MohammadTaghi Hajiaghayi, Suho Shin +1
We study social learning dynamics motivated by reviews on online platforms. The agents collectively follow a simple multi-armed bandit protocol, but each agent acts myopically, wit…
Multi-armed Bandit Algorithm against Strategic Replication
Suho Shin, Seungjoon Lee, Jungseul Ok
We consider a multi-armed bandit problem in which a set of arms is registered by each agent, and the agent receives reward when its arm is selected. An agent might strategically su…
Power of Bonus in Pricing for Crowdsourcing
Suho Shin, Hoyong Choi, Yung Yi +1
We consider a simple form of pricing for a crowdsourcing system, where pricing policy is published a priori, and workers then decide their task acceptance. Such a pricing form is w…