2 citations · 4 across the 16 of their papers we have counts for
5 papers · 1 filter
Mitigating LLM sycophancy with RL-based fine-tuning: Bayesian Truth Serum approach
Serhii Mytsyk, Yiming Zhang, Vikram Krishnamurthy
Large language models (LLMs) frequently exhibit \emph{sycophancy}: they adapt their answers to a user's stated beliefs or preferences instead of reporting what they hold to be true…
Interacting Large Language Model Agents. Interpretable Models and Social Learning
Adit Jain, Vikram Krishnamurthy
This paper discusses the theory and algorithms for interacting large language model agents (LLMAs) using methods from statistical signal processing and microeconomics. While both f…
Sparse Linear Bandits with Blocking Constraints
Adit Jain, Soumyabrata Pal, Sunav Choudhary +3
We investigate the high-dimensional sparse linear bandits problem in a data-poor regime where the time horizon is much smaller than the ambient dimension and number of arms. We stu…
Structured Reinforcement Learning for Incentivized Stochastic Covert Optimization
Adit Jain, Vikram Krishnamurthy
This paper studies how a stochastic gradient algorithm (SG) can be controlled to hide the estimate of the local stationary point from an eavesdropper. Such problems are of signific…
Who You Play Affects How You Play: Predicting Sports Performance Using Graph Attention Networks With Temporal Convolution
Rui Luo, Vikram Krishnamurthy
This study presents a novel deep learning method, called GATv2-GCN, for predicting player performance in sports. To construct a dynamic player interaction graph, we leverage player…