works on

From the 2 of 18 linked papers with an AI index.

activity
20242026
collaborators

18 papers

cs.AR2026

MDTransformer: A Hardware-Software Co-Design of Mode-Division Photonic Transformer Accelerator with Inverse-Designed Coherent Crossbar

Solomon Micheal Serunjogi, Rachmad Vidya Wicaksana Putra, Ayat Taha +2

MDTransformer is a hardware-software co-designed photonic accelerator that uses mode-division multiplexing and inverse-designed optical components to perform complex matrix multipl…

cs.NE2026

Enabling Energy-Efficient Simultaneous Multi-Task Reinforcement Learning through Spiking Neural Networks with Active Dendrites for Bio-inspired Generalist Agents

Rachmad Vidya Wicaksana Putra, Avaneesh Devkota, Muhammad Shafique

The paper introduces MTSpark, a method that combines spiking neural networks with active dendrites to enable energy‑efficient simultaneous multi‑task reinforcement learning, achiev…

cs.NE2026

AQ4SViT: An Automated Quantization Framework with Search Gating Policy for Compressing Spiking Vision Transformers

Rachmad Vidya Wicaksana Putra, Saad Iftikhar, Muhammad Shafique

Spiking Vision Transformers (SViTs) have emerged as alternative low-power ViT models, but their large sizes hinder their deployments on resource-constrained embedded AI systems. To…

cs.LG2026

QuBLAST: A Framework for Quantizing Large Language Models with Block-Level Compression Approach and Activation Scaling Strategy

Pasindu Wickramasinghe, Achyuta Muthuvelan, Rachmad Vidya Wicaksana Putra +2

LLMs have become the state-of-the-art algorithms for solving NLP tasks. However, they typically come at huge computational and memory costs, thus making them difficult to deploy on…

cs.AR2026

DxPTA: An Architecture Design Space Exploration with Optical Dataflow-guided Strategy for HW/SW Co-Design of Photonic Transformer Accelerators

Rachmad Vidya Wicaksana Putra, Solomon Micheal Serunjogi, Mahmoud Rasras +1

Transformer-based networks have emerged as prominent AI models with state-of-the-art performance, which potentially pave the way toward artificial general intelligence (AGI). Howev…

cs.NE2026

PrimeSVT: An Automated Memory-aware Pruning Framework with Prioritized Compression Policy for Spiking Vision Transformers

Rachmad Vidya Wicaksana Putra, Achyuta Muthuvelan, Alberto Marchisio +1

The large sizes of Spiking Vision Transformers (SViTs) still hinder their embedded implementation, highlighting the need for model compression. State-of-the-art works compress SViT…