most citedQ-S5: Towards Quantized State Space Models

2 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20241 cited

PARSE-Ego4D: Personal Action Recommendation Suggestions for Egocentric Videos

Steven Abreu, Tiffany D. Do, Karan Ahuja +4

Intelligent assistance involves not only understanding but also action. Existing ego-centric video datasets contain rich annotations of the videos, but not of actions that an intel…

cs.LG2024

Mamba-PTQ: Outlier Channels in Recurrent Large Language Models

Alessandro Pierro, Steven Abreu

Modern recurrent layers are emerging as a promising path toward edge deployment of foundation models, especially in the context of large language models (LLMs). Compressing the who…

cs.LG20242 cited

Q-S5: Towards Quantized State Space Models

Steven Abreu, Jens E. Pedersen, Kade M. Heckel +1

In the quest for next-generation sequence modeling architectures, State Space Models (SSMs) have emerged as a potent alternative to transformers, particularly for their computation…

cs.NE2023

Concepts and Paradigms for Neuromorphic Programming

Steven Abreu

The value of neuromorphic computers depends crucially on our ability to program them for relevant tasks. Currently, neuromorphic computers are mostly limited to machine learning me…

cs.NE20231 cited

Training a spiking neural network on an event-based label-free flow cytometry dataset

Muhammed Gouda, Steven Abreu, Alessio Lugnan +1

Imaging flow cytometry systems aim to analyze a huge number of cells or micro-particles based on their physical characteristics. The vast majority of current systems acquire a larg…