collaborators

15 papers

cs.LG2026

Sample Complexity of Multicalibration for Multilevel Properties

Jiuyao Lu, Krishnakumar Balasubramanian, Aleksandr Podkopaev +1

Calibration requires a predictor to be unbiased after conditioning on its own predictions. Multicalibration asks for this guarantee simultaneously across a collection of groups. Ma…

cs.LG2026

FoundCause: Causal Discovery with Latent Confounders from Observational Data

Patrick Blöbaum, Krishnakumar Balasubramanian, Shiva Prasad Kasiviswanathan

Causal discovery from observational data remains challenging due to the need to recover directed structure and latent confounding without interventions. We propose FoundCause, an a…

cs.CL2026

Measuring Semantic Progress in Multi-turn Dialogue via Information Gain

Paul He, Shiva Kasiviswanathan, Dominik Janzing

Evaluating multi-turn dialogue is challenging because quality emerges across turns rather than within individual responses. We focus on a key dimension of information-seeking dialo…

cs.LG2026

A Quantitative Characterization of Forgetting in Post-Training

Krishnakumar Balasubramanian, Shiva Prasad Kasiviswanathan

Continual post-training of generative models is widely used, yet a principled understanding of when and why forgetting occurs remains limited. We develop theoretical results under…

cs.CL2026

Training Large Language Models To Reason In Parallel With Global Forking Tokens

Sheng Jia, Xiao Wang, Shiva Prasad Kasiviswanathan

Although LLMs have demonstrated improved performance by scaling parallel test-time compute, doing so relies on generating reasoning paths that are both diverse and accurate. For ch…

cs.LG2026

Learning to Answer from Correct Demonstrations

Nirmit Joshi, Gene Li, Siddharth Bhandari +3

We study the problem of learning to generate an answer (or completion) to a question (or prompt), where there could be multiple correct answers, any one of which is acceptable at t…