5 papers
One Lens, Many Worlds : A Capability-Typed Interface for World-Model Interpretability
Bhavith Chandra Challagundla, Sanskar Pandey, Param Thakkar +7
World models are now built on substantially different computational substrates. Latent recurrent state-space models such as PlaNet and the Dreamer family compress observations into…
BhashaSetu: A Data-Centric Approach to Low-Resource Machine Translation
Param Thakkar, Anushka Yadav, Michael Tiemann +3
We present BhashaSetu, a linguistically enriched English--Marathi parallel dataset addressing persistent data limitations in low-resource neural machine translation (NMT). Marathi,…
HELIX: Scaling Raw Audio Understanding with Hybrid Mamba-Attention Beyond the Quadratic Limit
Khushiyant, Param Thakkar
Audio representation learning typically evaluates design choices such as input frontend, sequence backbone, and sequence length in isolation. We show that these axes are coupled, a…
BenchRL-QAS: Benchmarking reinforcement learning algorithms for quantum architecture search
Azhar Ikhtiarudin, Aditi Das, Param Thakkar +1
We present BenchRL-QAS, a unified benchmarking framework for reinforcement learning (RL) in quantum architecture search (QAS) across a spectrum of variational quantum algorithm tas…
Personalized Recommendation Systems using Multimodal, Autonomous, Multi Agent Systems
Param Thakkar, Anushka Yadav
This paper describes a highly developed personalised recommendation system using multimodal, autonomous, multi-agent systems. The system focuses on the incorporation of futuristic…