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              <text>Low Earth Orbit (LEO) extends up to 2000km above the Earth’s surface and is under threat of overcrowding from satellite megaconstellation projects, such as Starlink. This study investigates different methods for monitoring Starlink satellites by comparing the performance of telescope array case studies to the all-sky array, which uses thousands of telescopes to monitor the entire sky from a single site. By analysing key metrics, I demonstrate significant benefits for using a global network of telescope arrays over the all-sky array, particularly in terms of cost-effectiveness.</text>
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              <text>As the adoption of Large Language Models (LLMs) is becoming ubiquitous, understanding their pitfalls is becoming increasingly urgent. LLMs are known to hallucinate and may be subject to cascading hallucinatory generations due to their autoregressive structure and exposure bias. This paper first introduces the topic of hallucination cascade, covering relevant literature. Then an experiment is presented on the propagation of hallucination through long answer text generation, for all combinations of five LLMs - Qwen2 (0.5B), Qwen2 (7B), Llama3.1 (8B), Gemma2 (9B) and Mistral-NeMo (12B) - at five levels of temperature: 0, 0.75, 1, 1.25, 2. In a novel methodology, responses are generated by the five LLMs, then labelled by two more LLMs as hallucinatory or not on both a token and sentence level. The labelling is done with clear instructions and additional context to ensure its quality. Correlational evidence was found on both granularity levels that hallucinatory tokens are positively autocorrelated at lag 1, and that autocorrelation monotonically decreases as lag increases (token level only), supporting the cascading hallucination hypothesis. Finally, some hallucination mitigating techniques are presented, with both research and application in mind. All the code used for the empirical part of this paper (Section 3) can be found at https://github.com/LucMekouar/URSS_2024.</text>
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