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S. Kasiviswanathan

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Preprint Oct 2026

A Dimension-Free Bound on the Poincar\'e Constant of Isotropic Log-Concave Measures

The Kannan--Lov\'asz--Simonovits (KLS) conjecture asserts that isotropic log-concave probability measures have Poincar\'e constants bounded by a universal constant, independently of dimension. We give a deterministic variational proof with an explicit bound on the Poincar\'e constant $C_P(\mu)\le25$, where $\mu$ is any...

K. Balasubramanian, S. Kasiviswanathan · 0 citations
#machine learning Preprint Oct 2026

Read What Matters: Query-Adaptive Quantization for KV Caches

KV-cache entries are stored before their future queries are known, but each decoding query needs precision in different places. We study this mismatch using separate budgets for retained bits and bits fetched per query. ReadKV stores each key and value in a progressive code whose prefixes support different reconstructi...

Siddharth Bhandari, Lucas Gretta, K. Balasubramanian et al. · 0 citations
#artificial intelligence Preprint Oct 2026

Counterfactual Generation via Flow Matching: Coupling-Sensitive End-to-End Rates

Counterfactual generation seeks to sample outcomes under a hypothetical intervention or decision using observational data collected under the factual assignment mechanism. We develop a flow-matching approach that combines a sample-split, doubly robust training objective with a learned coupling between observed source o...

Yun-Rui Guan, K. Balasubramanian, S. Kasiviswanathan · 0 citations
#machine learning Preprint Aug 2026

Group Adaptive Clipping Policy Optimization

Group Adaptive Clipping Policy Optimization (GAPO), a plug-in modification to GRPO methods that adapts the clipping boundary to the rollout advantage, is proposed, motivated by a reverse-KL trust-region perspective, which suggests that rollouts with larger learning signal should receive proportionally greater update he...

Sheng Jia, Xiao Wang, S. Kasiviswanathan et al. · 0 citations

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