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Found 4 papers, 0 papers with code
Interacting Large Language Model Agents. Interpretable Models and Social Learning
The main takeaway of this paper, based on substantial empirical analysis and mathematical formalism, is that LLMAs act as rationally bounded Bayesian agents that exhibit social learning when interacting.
Annotation Efficiency: Identifying Hard Samples via Blocked Sparse Linear Bandits
This paper considers the problem of annotating datapoints using an expert with only a few annotation rounds in a label-scarce setting.
Structured Reinforcement Learning for Incentivized Stochastic Covert Optimization
This paper studies how a stochastic gradient algorithm (SG) can be controlled to hide the estimate of the local stationary point from an eavesdropper.
Controlling Federated Learning for Covertness
The problem of controlling the stochastic gradient algorithm for covert optimization is modeled as a Markov decision process, and we show that the dynamic programming operator has a supermodular structure implying that the optimal policy has a monotone threshold structure.
