Found 8 document(s)
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Reliable evaluation of LLM-based alpha mining requires more than positive backtest summaries. We audit a preserved project at three levels: historical run counters, outcome retention, and a separately scoped public reana...
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Machine learning (ML) is increasingly used in astronomy, but choosing a suitable method for a scientific problem often requires expertise in both astronomy and ML. Large language models (LLMs) could help astronomers make...
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AI agents now run experiments and report findings, so research produces claims faster than researchers can check them. Each empirical claim implies a property that must hold over its cases, but it states that property on...
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Large language models (LLMs) can produce plausible but incorrect answers when they are uncertain, which can mislead users and undermine model reliability. Training models to abstain with reinforcement learning is a natur...
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Recent advances in generative video models have improved visual realism, making detection increasingly dependent on subtle temporal inconsistencies. However, these signals are weak and spatially localized, while most of ...
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With the rapid development of economic globalization and educational internationalization, overseas education has emerged as a pivotal trend in the current global education landscape. Employing bibliometric methods, this...
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Current deep learning methods such as convolutional neural networks (CNNs) are often dedicated to a specific task and object; they are generally fixed in network architecture, which limits their generalizability and prev...
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The MAC methodology consists of using a protected hydroxymalononitrile derivative as an umpolung reagent to allow the insertion of a carbonyl function between an electrophile and a nucleophile. This thesis is devoted to ...