collaborators

7 papers

cs.CL2026

IKS-Instruct: A 24,000-Example Multilingual Dataset for Teaching Language Models Indian Knowledge Systems

Shwetha Singaravelu, Gayathri Muruganantham, Lakshmi Rajendran +1

Instruction tuning has become the standard method for adapting large language models to follow human intent, yet existing instruction datasets are dominated by English-language gen…

cs.CL2026

BHARATI: Morphology-Aware Tokenizers for Classical Indian Languages with Subword Fertility Analysis

Poornima Kumaresan, Pavithra Muruganantham, Lakshmi Rajendran +1

Standard subword tokenization algorithms such as Byte-Pair Encoding (BPE) and SentencePiece are trained predominantly on modern language corpora and produce inefficient segmentatio…

cs.ET2026

An Open-Source LFSR-Based Stochastic Leaky Integrate-and-Fire Neuron in SkyWater 130 nm: Design, Stochastic Characterisation, and Rate Coding

Poornima Kumaresan, Santhosh Sivasubramani

Stochastic spiking neurons trade exact arithmetic for controlled randomness, lowering area and tolerating input noise, which suits event-driven edge hardware. We present a compact,…

cs.ET2026

Design and Development of a Neuromorphic Silicon Suite: PVT Sensing, Stochastic LIF Inference, On-Chip STDP Learning, and Crossbar Programming

Poornima Kumaresan, Santhosh Sivasubramani

Edge neuromorphic systems need compact, configurable hardware that combines probabilistic inference, local learning, and an interface to emerging analogue memory. We present four i…

cs.ET2026

Eliminating Vendor Lock-In in Quantum Machine Learning via Framework-Agnostic Neural Networks

Poornima Kumaresan, Shwetha Singaravelu, Lakshmi Rajendran +1

Quantum machine learning (QML) stands at the intersection of quantum computing and artificial intelligence, offering the potential to solve problems that remain intractable for cla…

cs.ET2026

Adaptive Tensor Network Simulation via Entropy-Feedback PID Control and GPU-Accelerated SVD

Harshni Kumaresan, Gayathri Muruganantham, Lakshmi Rajendran +1

Tensor network methods, particularly those based on Matrix Product States (MPS), provide a powerful framework for simulating quantum many-body systems. A persistent computational c…