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Initializing Services in Interactive ML Systems for Diverse Users
Neural Information Processing Systems
This paper investigates ML systems serving a group of users, with multiple models/services, each aimed at specializing to a sub-group of users.
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No-Regret Learning for Fair Multi-Agent Social Welfare Optimization
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We consider the problem of online multi-agent Nash social welfare (NSW) maximization.
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NYU CTF Bench: A Scalable Open-Source Benchmark Dataset for Evaluating LLMs in Offensive Security
Neural Information Processing Systems
Large Language Models (LLMs) are being deployed across various domains today. However, their capacity to solve Capture the Flag (CTF) challenges in cybersecurity has not been thoroughly evaluated.
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A Metalearned Neural Circuit for Nonparametric Bayesian Inference
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Most applications of machine learning to classification assume a closed set of balanced classes.
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Geometric-A veraged Preference Optimization for Soft Preference Labels
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However, human preferences can vary across individuals, and therefore should be represented distributionally.
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