Memory constraints remain a critical bottleneck in the deployment of large-scale AI models. Parameter sharing across network depth reduces model storage, but repeatedly applying an identical transformation limits flexibility across layers. Inspired by time--memory trade-offs in classical algorithms, we introduce the Li...
This article experimentally evaluates whether large language models (LLMs) can generate operationally realistic ATC transmissions and outlines a concrete path and its current limits toward LLM-assisted ATC.
Mahyar Ghazanfari, Matthias Casanova, J. Kam et al.· 1 citation
It is shown that paragraph supervision enables effective use of long token sequences, whereas caption-only training degrades beyond 60 tokens, and paragraph supervision consistently benefits long-description benchmarks and hard negatives prove detrimental in text-only fine-tuning.
Mahyar Ghazanfari, Amin Tabrizian, Arsyi Aziz et al.· 0 citations
FRAMe signifies how advanced LLMs can be deployed for human-centric mission planning, translating natural language instructions into safe, efficient, and flexible flight routes.
Amin Tabrizian, Arsyi Aziz, Aarifah Ullah et al.· 1 citation
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