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From the 1 of 14 linked papers with an AI index.

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14 papers

cs.CV2026

FOLIO: Focused Semantic Memory for Streaming Video Understanding

Haoyang Fan, Dhruv Parikh, Anvitha Ramachandran +4

The paper introduces FOLIO, a training‑free focused semantic memory system that records detailed information about important entities in a streaming video while compactly storing s…

cs.CV2026

Vision Non-Causal Trapezoidal Mamba: Eliminating Directional Scanning in Vision SSMs with Second-Order Dynamics

Anvitha Ramachandran, Dhruv Parikh, Haoyang Fan +2

State Space Models (SSMs) have emerged as an alternative to Vision Transformers, yet most vision SSMs inherit directional token scanning from causal sequence modeling. While effect…

cs.AR2026

Efficient and Accurate Graph Classification with Hyperdimensional Computing on FPGA

Jebacyril Arockiaraj, Dhruv Parikh, Viktor Prasanna

Real-time, energy-efficient inference on edge devices is essential for graph classification across a range of applications. Hyperdimensional Computing (HDC) is a brain-inspired com…

cs.CV2026

Latent Denoising Improves Visual Alignment in Large Multimodal Models

Dhruv Parikh, Jacob Fein-Ashley, Rajgopal Kannan +1

Large Multimodal Models (LMMs) such as LLaVA are typically trained with an autoregressive language modeling objective, providing only indirect supervision to visual tokens. This of…

cs.CV2026

GraphLeap: Decoupling Graph Construction and Convolution for Vision GNN Acceleration on FPGA

Anvitha Ramachandran, Dhruv Parikh, Viktor Prasanna

Vision Graph Neural Networks (ViGs) represent an image as a graph of patch tokens, enabling adaptive, feature-driven neighborhoods. Unlike CNNs with fixed grid biases or Vision Tra…

cs.CV2026

ImageHD: Energy-Efficient On-Device Continual Learning of Visual Representations via Hyperdimensional Computing

Jebacyril Arockiaraj, Dhruv Parikh, Viktor Prasanna

On-device continual learning (CL) is critical for edge AI systems operating on non-stationary data streams, but most existing methods rely on backpropagation or exemplar-heavy clas…