5 accepted papers
When exploring complex unknown environments, unmanned aerial vehicles (UAVs) often experience reduced efficiency and robustness due to unevenly distributed occlusions. This paper proposes an efficient hybrid autonomous exploration algorithm that adapts to environmental complexity, enabling effective…
In order to address the high complexity and low efficiency of amphibious propulsion systems, this paper proposes a novel variable wheel-propeller integrated mechanism for amphibious robots. By adjusting the blade pitch angle, it enables multiple motion modes, including rapid and stable movement on f…
Addressing intermittent client availability is critical for the real-world deployment of federated learning algorithms. Most prior work either overlooks the potential non-stationarity in the dynamics of client unavailability or requires substantial memory/computation overhead. We study federated lea…
It is an open question what semantic representations transformer-based language models can encode and whether they have access to more abstract aspects of semantic meaning. Here, we propose a diagnostic dataset to investigate how well language models understand the degree semantics of adjectives. In…
Natural language inference (NLI) is a task to infer the relationship between a premise and a hypothesis (e.g., entailment, neutral, or contradiction), and transformer-based models perform well on current NLI datasets such as MNLI and SNLI. Nevertheless, given the linguistic complexity of the large-s…