5 papers
Total Variation Rates for Riemannian Flow Matching
Yunrui Guan, Krishnakumar Balasubramanian, Shiqian Ma
Riemannian flow matching (RFM) extends flow-based generative modeling to data supported on manifolds by learning a time-dependent tangent vector field whose flow-ODE transports a s…
Dependence-Aware Label Aggregation for LLM-as-a-Judge via Ising Models
Krishnakumar Balasubramanian, Aleksandr Podkopaev, Shiva Prasad Kasiviswanathan
Large-scale AI evaluation increasingly relies on aggregating binary judgments from annotators, including LLMs used as judges. Most classical methods, e.g., Dawid-Skene or (weig…
On the Structure of Stationary Solutions to McKean-Vlasov Equations with Applications to Noisy Transformers
Krishnakumar Balasubramanian, Sayan Banerjee, Philippe Rigollet
We study stationary solutions of McKean-Vlasov equations on the circle. Our main contributions stem from observing an exact equivalence between solutions of the stationary McKean-V…
Statistical Inference for Linear Functionals of Online Least-squares SGD when
Bhavya Agrawalla, Krishnakumar Balasubramanian, Promit Ghosal
Stochastic Gradient Descent (SGD) has become a cornerstone method in modern data science. However, deploying SGD in high-stakes applications necessitates rigorous quantification of…
Restricted Spectral Gap Decomposition for Simulated Tempering Targeting Mixture Distributions
Jhanvi Garg, Krishna Balasubramanian, Quan Zhou
Simulated tempering is a widely used strategy for sampling from multimodal distributions. In this paper, we consider simulated tempering combined with an arbitrary local Markov cha…