arXiv subjects

Swathi Narashiman

Publications and source records attributed to Swathi Narashiman.

3 recordsLinked to original sources

arXiv2025

Genre Controlled Music Generation via Activation Steering

Computational Music Generation is evolving towards non-conventional styles, demanding methods that enable precise and controllable blending of diverse music elements. In this work, we present a method for fine grained control using inference-time interventions on an autoregressive generative transformer, MusicGen. Through our approach, we achieve genre control by steering the residual stream using weights of a linear probe on it. By framing activation steering as a human-controllable interaction, our work highlights how interpretable model behaviors can empower in co-creative music generation.Audio samples demonstrating our method are available on our demo page.

cs.SD↗

arXiv2025

3D Object Reconstruction with mmWave Radars

This paper presents RFconstruct, a framework that enables 3D shape reconstruction using commercial off-the-shelf (COTS) mmWave radars for self-driving scenarios. RFconstruct overcomes radar limitations of low angular resolution, specularity, and sparsity in radar point clouds through a holistic system design that addresses hardware, data processing, and machine learning challenges. The first step is fusing data captured by two radar devices that image orthogonal planes, then performing odometry-aware temporal fusion to generate denser 3D point clouds. RFconstruct then reconstructs 3D shapes of objects using a customized encoder-decoder model that does not require prior knowledge of the object's bound box. The shape reconstruction performance of RFconstruct is compared against 3D models extracted from a depth camera equipped with a LiDAR. We show that RFconstruct can accurately generate 3D shapes of cars, bikes, and pedestrians.

eess.IV↗

arXiv2024

Chiplets on Wheels: Review Paper on Holistic Chiplet Solutions for Autonomous Vehicles

On the advent of the slow death of Moore's law, the silicon industry is moving towards a new era of chiplets. The automotive industry is experiencing a profound transformation towards software-defined vehicles, fueled by the surging demand for automotive compute chips, expected to reach 20-22 billion by 2030. High-performance compute (HPC) chips become instrumental in meeting the soaring demand for computational power. Various strategies, including centralized electrical and electronic architecture and the innovative Chiplet Systems, are under exploration. The latter, breaking down System-on-Chips (SoCs) into functional units, offers unparalleled customization and integration possibilities. The research accentuates the crucial open Chiplet ecosystem, fostering collaboration and enhancing supply chain resilience. In this paper, we address the unique challenges that arise when attempting to leverage chiplet-based architecture to design a holistic silicon solution for the automotive industry. We propose a throughput-oriented micro-architecture for ADAS and infotainment systems alongside a novel methodology to evaluate chiplet architectures. Further, we develop in-house simulation tools leveraging the gem5 framework to simulate latency and throughput. Finally, we perform an extensive design of thermally-aware chiplet placement and develop a micro-fluids-based cooling design.

cs.AR↗