Author

N. Vijaykumar

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Preprint Sep 2026

KerColle: Unlocking Fine-Grained GPU Concurrency in Vision-Language-Action Models

Vision-Language-Action (VLA) models have emerged as foundational models for next-generation robotics. High VLA inference throughput is critical for meeting the control-rate requirements of robots. VLA models comprise two phases, a vision-language model (VLM) and an action head, that can be decoupled and executed asynch...

A. Li, Christina Giannoula, N. Vijaykumar · 0 citations

#machine learning Preprint Jun 2025

Squeeze3D: Extreme Neural Compression with Latent Space Bridging

Squeeze3D is a novel framework that leverages implicit prior knowledge learnt by existing pre-trained encoders and decoders to compress 3D data at extremely high compression ratios and can flexibly support different formats, including meshes, point clouds, and radiance fields.

Rishit Dagli, Yu-Shi Guan, Sankeerth Durvasula et al. · 0 citations

Preprint Jul 2026

zkComposer: Decomposing Proof Construction to Scale zkML

Zero-knowledge machine learning (zkML) enables a server to perform verifiable inference while keeping model parameters private from the client. However, existing zkML systems incur prohibitive proof-generation costs. We observe that proof generation exhibits limited parallelism; that is, prover time does not decrease s...

Pawan Kumar Sanjaya, Christina Giannoula, Valdy Oktavian et al. · 0 citations