2 citations · 2 across the 6 of their papers we have counts for
10 papers
When Does Tool Use Increase the Expressive Power of Finite-Precision Recurrent Models?
Nikola Zubić, Qian Li, Yuyi Wang +1
Modern sequence models are increasingly deployed as agents that interleave token generation with calls to external tools. We give an exact, architecture-level account of when such…
On the Expressive Power and Limitations of Multi-Layer SSMs
Nikola Zubić, Qian Li, Yuyi Wang +1
We study how depth, finite precision, state dimension, and chain-of-thought (CoT) affect the expressive power of multi-layer state-space models (SSMs). For the explicit-table -f…
Low-Latency Event-Based Object Detection with Spatially-Sparse Linear Attention
Haiqing Hao, Zhipeng Sui, Rong Zou +4
Event cameras provide sequential visual data with spatial sparsity and high temporal resolution, making them attractive for low-latency object detection. Existing asynchronous even…
Regularity and Stability Properties of Selective SSMs with Discontinuous Gating
Nikola Zubić, Davide Scaramuzza
Selective State-Space Models (SSMs) such as Mamba have become central to long-sequence modeling. Still, their stability is poorly understood: their state-space coefficients are mod…
Maximizing Asynchronicity in Event-based Neural Networks
Haiqing Hao, Nikola Zubić, Weihua He +3
Event cameras deliver visual data with high temporal resolution, low latency, and minimal redundancy, yet their asynchronous, sparse sequential nature challenges standard tensor-ba…
Perturbed State Space Feature Encoders for Optical Flow with Event Cameras
Gokul Raju Govinda Raju, Nikola Zubić, Marco Cannici +1
With their motion-responsive nature, event-based cameras offer significant advantages over traditional cameras for optical flow estimation. While deep learning has improved upon tr…