4 accepted papers
Existing end-to-end speech large language models (LLMs) usually rely on large-scale annotated data for training, while data-efficient training has not been discussed in depth. We focus on two fundamental problems between speech and text: the representation space gap and sequence length inconsistency…
Pedestrian detection is an important task for human-robot interaction and autonomous driving applications. Most previous pedestrian detection methods rely on data collected from three-dimensional (3D) Light Detection and Ranging (LiDAR) sensors in addition to camera imagery, which can be expensive t
In this paper we propose a novel metric of basketball game success, derived from a team’s dynamic social network of game play. We combine ideas from random effects models for network links with taking a multi-resolution stochastic process approach to model passes between teammates. These passes can…
As autonomous robots increasingly become part of daily life, they will often encounter dynamic environments while only having limited information about their surroundings. Unfortunately, due to the possible presence of malicious dynamic actors, it is infeasible to develop an algorithm that can guara…