1 citations · 4 across the 7 of their papers we have counts for
4 papers · 1 filter
Pooling Helps, Learned Weighting Hurts In-Context: Decomposing Group Attention
Michael Fore, James Mason Inder, Mrishika Nair +2
Group attention, introduced by the time series forecasting model Chronos-2, attends over the variates of a group at a fixed patch index and serves both multivariate (MV) and in-con…
Non-Parametric Spatiotemporal Trajectory Prediction via State-Conditioned Transition Sampling
Michael Fore, Akshay Jain, Justin Downes +2
We present a training-free method for multi-modal trajectory prediction that achieves comparable accuracy to a 57M-parameter transformer while requiring no GPU and zero learned par…
Multi-Agent Geospatial Copilots for Remote Sensing Workflows
Chaehong Lee, Varatheepan Paramanayakam, Andreas Karatzas +7
We present GeoLLM-Squad, a geospatial Copilot that introduces the novel multi-agent paradigm to remote sensing (RS) workflows. Unlike existing single-agent approaches that rely on…
GeckOpt: LLM System Efficiency via Intent-Based Tool Selection
Michael Fore, Simranjit Singh, Dimitrios Stamoulis
In this preliminary study, we investigate a GPT-driven intent-based reasoning approach to streamline tool selection for large language models (LLMs) aimed at system efficiency. By…